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Software-Defined Network Frameworks : Security Issues and Use Cases (Computational Intelligence Techniques)

By: Mandeep Kaur (Edited by) , Mandeep Kaur (Edited by) , Mandeep Kaur (Edited by) , Mandeep Kaur (Edited by) , Mandeep Kaur (Edited by) , Mandeep Kaur (Edited by) , Mandeep Kaur (Edited by) , Mandeep Kaur (Edited by) , Mandeep Kaur (Edited by) , Mandeep Kaur (Edited by) , Mandeep Kaur (Edited by) , Mandeep Kaur (Edited by) , Mandeep Kaur (Edited by) , Mandeep Kaur (Edited by) , Mandeep Kaur (Edited by) , Mandeep Kaur (Edited by) , Mandeep Kaur (Edited by) , Mandeep Kaur (Edited by) , Mandeep Kaur (Edited by) , Mandeep Kaur (Edited by) , Mandeep Kaur (Edited by) , Mandeep Kaur (Edited by) , Mandeep Kaur (Edited by) , Mandeep Kaur (Edited by) , Mandeep Kaur (Edited by) , Mandeep Kaur (Edited by) , Mandeep Kaur (Edited by) , Mandeep Kaur (Edited by) , Mandeep Kaur (Edited by) , Mandeep Kaur (Edited by) , Mandeep Kaur (Edited by) , Mandeep Kaur (Edited by) , Mandeep Kaur (Edited by) , Mandeep Kaur (Edited by) , Mandeep Kaur (Edited by) , Mandeep Kaur (Edited by) , Mandeep Kaur (Edited by) , Mandeep Kaur (Edited by) , Mandeep Kaur (Edited by) , Mandeep Kaur (Edited by) , Mandeep Kaur (Edited by) , Mandeep Kaur (Edited by) , Mandeep Kaur (Edited by) , Mandeep Kaur (Edited by) , Mandeep Kaur (Edited by) , Mandeep Kaur (Edited by) , Mandeep Kaur (Edited by) , Mandeep Kaur (Edited by) , Mandeep Kaur (Edited by) , Mandeep Kaur (Edited by) , Mandeep Kaur (Edited by) , Mandeep Kaur (Edited by) , Mandeep Kaur (Edited by) , Mandeep Kaur (Edited by) , Mandeep Kaur (Edited by) , Mandeep Kaur (Edited by) , Mandeep Kaur (Edited by) , Mandeep Kaur (Edited by) , Mandeep Kaur (Edited by) , Mandeep Kaur (Edited by) , Mandeep Kaur (Edited by) , Mandeep Kaur (Edited by) , Mandeep Kaur (Edited by) , Mandeep Kaur (Edited by) , Mandeep Kaur (Edited by) , Mandeep Kaur (Edited by) , Mandeep Kaur (Edited by) , Mandeep Kaur (Edited by) , Mandeep Kaur (Edited by) , Mandeep Kaur (Edited by) , Mandeep Kaur (Edited by) , Mandeep Kaur (Edited by) , Mandeep Kaur (Edited by) , Mandeep Kaur (Edited by) , Mandeep Kaur (Edited by) , Mandeep Kaur (Edited by) , Mandeep Kaur (Edited by) , Mandeep Kaur (Edited by) , Mandeep Kaur (Edited by) , Mandeep Kaur (Edited by) , Mandeep Kaur (Edited by) , Mandeep Kaur (Edited by) , Mandeep Kaur (Edited by) , Mandeep Kaur (Edited by) , Mandeep Kaur (Edited by) , Mandeep Kaur (Edited by) , Mandeep Kaur (Edited by) , Mandeep Kaur (Edited by) , Mandeep Kaur (Edited by) , Mandeep Kaur (Edited by) , Mandeep Kaur (Edited by) , Mandeep Kaur (Edited by) , Mandeep Kaur (Edited by) , Mandeep Kaur (Edited by) , Mandeep Kaur (Edited by) , Mandeep Kaur (Edited by) , Mandeep Kaur (Edited by) , Mandeep Kaur (Edited by) , Mandeep Kaur (Edited by) , Mandeep Kaur (Edited by) , Mandeep Kaur (Edited by) , Mandeep Kaur (Edited by) , Mandeep Kaur (Edited by) , Mandeep Kaur (Edited by) , Mandeep Kaur (Edited by) , Mandeep Kaur (Edited by) , Mandeep Kaur (Edited by) , Mandeep Kaur (Edited by) , Mandeep Kaur (Edited by) , Mandeep Kaur (Edited by) , Mandeep Kaur (Edited by) , Mandeep Kaur (Edited by) , Mandeep Kaur (Edited by) , Mandeep Kaur (Edited by) , Mandeep Kaur (Edited by) , Mandeep Kaur (Edited by) , Mandeep Kaur (Edited by) , Mandeep Kaur (Edited by) , Mandeep Kaur (Edited by) , Mandeep Kaur (Edited by) , Mandeep Kaur (Edited by) , Mandeep Kaur (Edited by) , Mandeep Kaur (Edited by) , Mandeep Kaur (Edited by) , Mandeep Kaur (Edited by) , Mandeep Kaur (Edited by) , Mandeep Kaur (Edited by) , Mandeep Kaur (Edited by) , Mandeep Kaur (Edited by) , Mandeep Kaur (Edited by) , Mandeep Kaur (Edited by) , Mandeep Kaur (Edited by) , Mandeep Kaur (Edited by) , Mandeep Kaur (Edited by) , Mandeep Kaur (Edited by) , Mandeep Kaur (Edited by) , Mandeep Kaur (Edited by) , Mandeep Kaur (Edited by) , Mandeep Kaur (Edited by) , Mandeep Kaur (Edited by) , Mandeep Kaur (Edited by) , Mandeep Kaur (Edited by) , Mandeep Kaur (Edited by) , Mandeep Kaur (Edited by) , Mandeep Kaur (Edited by) , Mandeep Kaur (Edited by) , Mandeep Kaur (Edited by) , Mandeep Kaur (Edited by) , Mandeep Kaur (Edited by) , Mandeep Kaur (Edited by) , Mandeep Kaur (Edited by) , Mandeep Kaur (Edited by) , Mandeep Kaur (Edited by) , Mandeep Kaur (Edited by) , Mandeep Kaur (Edited by) , Mandeep Kaur (Edited by) , Mandeep Kaur (Edited by) , Mandeep Kaur (Edited by) , Mandeep Kaur (Edited by) , Mandeep Kaur (Edited by) , Mandeep Kaur (Edited by) , Mandeep Kaur (Edited by) , Mandeep Kaur (Edited by) , Mandeep Kaur (Edited by) , Mandeep Kaur (Edited by) , Mandeep Kaur (Edited by) , Mandeep Kaur (Edited by) , Mandeep Kaur (Edited by) , Mandeep Kaur (Edited by) , Mandeep Kaur (Edited by) , Mandeep Kaur (Edited by) , Mandeep Kaur (Edited by) , Mandeep Kaur (Edited by) , Mandeep Kaur (Edited by) , Mandeep Kaur (Edited by) , Mandeep Kaur (Edited by) , Mandeep Kaur (Edited by) , Mandeep Kaur (Edited by) , Mandeep Kaur (Edited by) , Mandeep Kaur (Edited by) , Mandeep Kaur (Edited by) , Mandeep Kaur (Edited by) , Mandeep Kaur (Edited by) , Mandeep Kaur (Edited by) , Mandeep Kaur (Edited by) , Mandeep Kaur (Edited by) , Mandeep Kaur (Edited by) , Mandeep Kaur (Edited by) , Mandeep Kaur (Edited by) , Mandeep Kaur (Edited by) , Mandeep Kaur (Edited by) , Mandeep Kaur (Edited by) , Mandeep Kaur (Edited by) , Mandeep Kaur (Edited by) , Mandeep Kaur (Edited by) , Mandeep Kaur (Edited by) , Mandeep Kaur (Edited by) , Mandeep Kaur (Edited by) , Mandeep Kaur (Edited by) , Mandeep Kaur (Edited by) , Mandeep Kaur (Edited by) , Mandeep Kaur (Edited by) , Mandeep Kaur (Edited by) , Mandeep Kaur (Edited by) , Mandeep Kaur (Edited by) , Mandeep Kaur (Edited by) , Mandeep Kaur (Edited by) , Mandeep Kaur (Edited by) , Mandeep Kaur (Edited by) , Mandeep Kaur (Edited by) , Mandeep Kaur (Edited by) , Mandeep Kaur (Edited by) , Mandeep Kaur (Edited by) , Mandeep Kaur (Edited by) , Mandeep Kaur (Edited by) , Mandeep Kaur (Edited by) , Mandeep Kaur (Edited by) , Mandeep Kaur (Edited by) , Mandeep Kaur (Edited by) , Mandeep Kaur (Edited by) , Mandeep Kaur (Edited by) , Mandeep Kaur (Edited by) , Mandeep Kaur (Edited by) , Mandeep Kaur (Edited by) , Mandeep Kaur (Edited by) , Mandeep Kaur (Edited by) , Mandeep Kaur (Edited by) , Mandeep Kaur (Edited by) , Mandeep Kaur (Edited by) , Mandeep Kaur (Edited by) , Mandeep Kaur (Edited by) , Mandeep Kaur (Edited by) , Mandeep Kaur (Edited by) , Mandeep Kaur (Edited by) , Mandeep Kaur (Edited by) , Mandeep Kaur (Edited by) , Mandeep Kaur (Edited by) , Mandeep Kaur (Edited by) , Mandeep Kaur (Edited by) , Mandeep Kaur (Edited by) , Mandeep Kaur (Edited by) , Mandeep Kaur (Edited by) , Mandeep Kaur (Edited by) , Mandeep Kaur (Edited by) , Mandeep Kaur (Edited by) , Mandeep Kaur (Edited by) , Mandeep Kaur (Edited by) , Mandeep Kaur (Edited by) , Mandeep Kaur (Edited by) , Mandeep Kaur (Edited by) , Mandeep Kaur (Edited by) , Mandeep Kaur (Edited by) , Mandeep Kaur (Edited by) , Mandeep Kaur (Edited by) , Mandeep Kaur (Edited by) , Mandeep Kaur (Edited by) , Mandeep Kaur (Edited by) , Mandeep Kaur (Edited by) , Mandeep Kaur (Edited by) , Mandeep Kaur (Edited by) , Mandeep Kaur (Edited by) , Mandeep Kaur (Edited by) , Mandeep Kaur (Edited by) , Mandeep Kaur (Edited by) , Nitin Rakesh (Edited by) , Nitin Rakesh (Edited by) , Nitin Rakesh (Edited by) , Nitin Rakesh (Edited by) , Nitin Rakesh (Edited by) , Nitin Rakesh (Edited by) , Nitin Rakesh (Edited by) , Nitin Rakesh (Edited by) , Nitin Rakesh (Edited by) , Nitin Rakesh (Edited by) , Nitin Rakesh (Edited by) , Nitin Rakesh (Edited by) , Nitin Rakesh (Edited by) , Nitin Rakesh (Edited by) , Nitin Rakesh (Edited by) , Nitin Rakesh (Edited by) , Nitin Rakesh (Edited by) , Nitin Rakesh (Edited by) , Nitin Rakesh (Edited by) , Nitin Rakesh (Edited by) , Nitin Rakesh (Edited by) , Nitin Rakesh (Edited by) , Nitin Rakesh (Edited by) , Nitin Rakesh (Edited by) , Nitin Rakesh (Edited by) , Nitin Rakesh (Edited by) , Nitin Rakesh (Edited by) , Nitin Rakesh (Edited by) , Nitin Rakesh (Edited by) , Nitin Rakesh (Edited by) , Nitin Rakesh (Edited by) , Nitin Rakesh (Edited by) , Nitin Rakesh (Edited by) , Nitin Rakesh (Edited by) , Nitin Rakesh (Edited by) , Nitin Rakesh (Edited by) , Nitin Rakesh (Edited by) , Nitin Rakesh (Edited by) , Nitin Rakesh (Edited by) , Nitin Rakesh (Edited by) , Nitin Rakesh (Edited by) , Nitin Rakesh (Edited by) , Nitin Rakesh (Edited by) , Nitin Rakesh (Edited by) , Nitin Rakesh (Edited by) , Nitin Rakesh (Edited by) , Nitin Rakesh (Edited by) , Nitin Rakesh (Edited by) , Nitin Rakesh (Edited by) , Nitin Rakesh (Edited by) , Nitin Rakesh (Edited by) , Nitin Rakesh (Edited by) , Nitin Rakesh (Edited by) , Nitin Rakesh (Edited by) , Nitin Rakesh (Edited by) , Nitin Rakesh (Edited by) , Nitin Rakesh (Edited by) , Nitin Rakesh (Edited by) , Nitin Rakesh (Edited by) , Nitin Rakesh (Edited by) , Nitin Rakesh (Edited by) , Nitin Rakesh (Edited by) , Nitin Rakesh (Edited by) , Nitin Rakesh (Edited by) , Nitin Rakesh (Edited by) , Nitin Rakesh (Edited by) , Nitin Rakesh (Edited by) , Nitin Rakesh (Edited by) , Nitin Rakesh (Edited by) , Nitin Rakesh (Edited by) , Nitin Rakesh (Edited by) , Nitin Rakesh (Edited by) , Nitin Rakesh (Edited by) , Nitin Rakesh (Edited by) , Nitin Rakesh (Edited by) , Nitin Rakesh (Edited by) , Nitin Rakesh (Edited by) , Nitin Rakesh (Edited by) , Nitin Rakesh (Edited by) , Nitin Rakesh (Edited by) , Nitin Rakesh (Edited by) , Nitin Rakesh (Edited by) , Nitin Rakesh (Edited by) , Nitin Rakesh (Edited by) , Nitin Rakesh (Edited by) , Nitin Rakesh (Edited by) , Nitin Rakesh (Edited by) , Nitin Rakesh (Edited by) , Nitin Rakesh (Edited by) , Nitin Rakesh (Edited by) , Nitin Rakesh (Edited by) , Nitin Rakesh (Edited by) , Nitin Rakesh (Edited by) , Nitin Rakesh (Edited by) , Nitin Rakesh (Edited by) , Nitin Rakesh (Edited by) , Nitin Rakesh (Edited by) , Nitin Rakesh (Edited by) , Nitin Rakesh (Edited by) , Nitin Rakesh (Edited by) , Nitin Rakesh (Edited by) , Nitin Rakesh (Edited by) , Nitin Rakesh (Edited by) , Nitin Rakesh (Edited by) , Nitin Rakesh (Edited by) , Nitin Rakesh (Edited by) , Nitin Rakesh (Edited by) , Nitin Rakesh (Edited by) , Nitin Rakesh (Edited by) , Nitin Rakesh (Edited by) , Nitin Rakesh (Edited by) , Nitin Rakesh (Edited by) , Nitin Rakesh (Edited by) , Nitin Rakesh (Edited by) , Nitin Rakesh (Edited by) , Nitin Rakesh (Edited by) , Nitin Rakesh (Edited by) , Nitin Rakesh (Edited by) , Nitin Rakesh (Edited by) , Nitin Rakesh (Edited by) , Nitin Rakesh (Edited by) , Nitin Rakesh (Edited by) , Nitin Rakesh (Edited by) , Nitin Rakesh (Edited by) , Nitin Rakesh (Edited by) , Nitin Rakesh (Edited by) , Nitin Rakesh (Edited by) , Nitin Rakesh (Edited by) , Nitin Rakesh (Edited by) , Nitin Rakesh (Edited by) , Nitin Rakesh (Edited by) , Nitin Rakesh (Edited by) , Nitin Rakesh (Edited by) , Nitin Rakesh (Edited by) , Nitin Rakesh (Edited by) , Nitin Rakesh (Edited by) , Nitin Rakesh (Edited by) , Nitin Rakesh (Edited by) , Nitin Rakesh (Edited by) , Nitin Rakesh (Edited by) , Nitin Rakesh (Edited by) , Nitin Rakesh (Edited by) , Nitin Rakesh (Edited by) , Nitin Rakesh (Edited by) , Nitin Rakesh (Edited by) , Nitin Rakesh (Edited by) , Nitin Rakesh (Edited by) , Nitin Rakesh (Edited by) , Nitin Rakesh (Edited by) , Nitin Rakesh (Edited by) , Nitin Rakesh (Edited by) , Nitin Rakesh (Edited by) , Nitin Rakesh (Edited by) , Nitin Rakesh (Edited by) , Nitin Rakesh (Edited by) , Nitin Rakesh (Edited by) , Nitin Rakesh (Edited by) , Nitin Rakesh (Edited by) , Nitin Rakesh (Edited by) , Nitin Rakesh (Edited by) , Nitin Rakesh (Edited by) , Nitin Rakesh (Edited by) , Nitin Rakesh (Edited by) , Nitin Rakesh (Edited by) , Nitin Rakesh (Edited by) , Nitin Rakesh (Edited by) , Nitin Rakesh (Edited by) , Nitin Rakesh (Edited by) , Nitin Rakesh (Edited by) , Nitin Rakesh (Edited by) , Nitin Rakesh (Edited by) , Nitin Rakesh (Edited by) , Nitin Rakesh (Edited by) , Nitin Rakesh (Edited by) , Nitin Rakesh (Edited by) , Nitin Rakesh (Edited by) , Nitin Rakesh (Edited by) , Nitin Rakesh (Edited by) , Nitin Rakesh (Edited by) , Nitin Rakesh (Edited by) , Nitin Rakesh (Edited by) , Nitin Rakesh (Edited by) , Nitin Rakesh (Edited by) , Nitin Rakesh (Edited by) , Nitin Rakesh (Edited by) , Nitin Rakesh (Edited by) , Nitin Rakesh (Edited by) , Nitin Rakesh (Edited by) , Nitin Rakesh (Edited by) , Nitin Rakesh (Edited by) , Nitin Rakesh (Edited by) , Nitin Rakesh (Edited by) , Nitin Rakesh (Edited by) , Nitin Rakesh (Edited by) , Nitin Rakesh (Edited by) , Nitin Rakesh (Edited by) , Nitin Rakesh (Edited by) , Nitin Rakesh (Edited by) , Nitin Rakesh (Edited by) , Nitin Rakesh (Edited by) , Nitin Rakesh (Edited by) , Nitin Rakesh (Edited by) , Nitin Rakesh (Edited by) , Nitin Rakesh (Edited by) , Nitin Rakesh (Edited by) , Nitin Rakesh (Edited by) , Nitin Rakesh (Edited by) , Nitin Rakesh (Edited by) , Nitin Rakesh (Edited by) , Nitin Rakesh (Edited by) , Nitin Rakesh (Edited by) , Nitin Rakesh (Edited by) , Nitin Rakesh (Edited by) , Nitin Rakesh (Edited by) , Nitin Rakesh (Edited by) , Nitin Rakesh (Edited by) , Nitin Rakesh (Edited by) , Nitin Rakesh (Edited by) , Nitin Rakesh (Edited by) , Nitin Rakesh (Edited by) , Nitin Rakesh (Edited by) , Nitin Rakesh (Edited by) , Nitin Rakesh (Edited by) , Nitin Rakesh (Edited by) , Nitin Rakesh (Edited by) , Nitin Rakesh (Edited by) , Nitin Rakesh (Edited by) , Nitin Rakesh (Edited by) , Nitin Rakesh (Edited by) , Nitin Rakesh (Edited by) , Nitin Rakesh (Edited by) , Nitin Rakesh (Edited by) , Nitin Rakesh (Edited by) , Nitin Rakesh (Edited by) , Nitin Rakesh (Edited by) , Nitin Rakesh (Edited by) , Nitin Rakesh (Edited by) , Nitin Rakesh (Edited by) , Nitin Rakesh (Edited by) , Nitin Rakesh (Edited by) , Nitin Rakesh (Edited by) , Nitin Rakesh (Edited by) , Nitin Rakesh (Edited by) , Nitin Rakesh (Edited by) , Nitin Rakesh (Edited by) , Nitin Rakesh (Edited by) , Nitin Rakesh (Edited by) , Nitin Rakesh (Edited by) , Nitin Rakesh (Edited by) , Nitin Rakesh (Edited by) , Nitin Rakesh (Edited by) , Nitin Rakesh (Edited by) , Nitin Rakesh (Edited by) , Nitin Rakesh (Edited by) , 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Manufacture on Demand

Ksh 30,400.00

Format: Hardback or Cased Book

ISBN-10: 1032450223

ISBN-13: 9781032450223

Collection / Series: Computational Intelligence Techniques

Collection Type: Publisher collection

Publisher: Taylor & Francis Ltd

Imprint: CRC Press

Country of Manufacture: GB

Country of Publication: GB

Publication Date: Apr 22nd, 2024

Publication Status: Active

Product extent: 310 Pages

Weight: 453.00 grams

Product Classification / Subject(s): Electrical engineering
WAP (wireless) technology
Environmental science, engineering & technology
Software Engineering
Computer security
Electrical engineering
WAP (wireless) technology
Environmental science, engineering & technology
Software Engineering
Computer security
Electrical engineering
WAP (wireless) technology
Environmental science, engineering & technology
Software Engineering
Computer security
Electrical engineering
WAP (wireless) technology
Environmental science, engineering & technology
Software Engineering
Computer security
Electrical engineering
WAP (wireless) technology
Environmental science, engineering & technology
Software Engineering
Computer security
Electrical engineering
WAP (wireless) technology
Environmental science, engineering & technology
Software Engineering
Computer security
Electrical engineering
WAP (wireless) technology
Environmental science, engineering & technology
Software Engineering
Computer security
Electrical engineering
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Environmental science, engineering & technology
Software Engineering
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Software Engineering
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Environmental science, engineering & technology
Software Engineering
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Software Engineering
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This book consolidates the research relating to the security in SDN, CSDN, and Hybrid SDNs. The security enhancements derived from use of various SDN frameworks and the security challenges thus introduced, are also discussed. Overall, this book explains different architectures of SDNs and the security challenges needs for implementing them.

Software-Defined Networks (SDN) work by virtualization of the network and the Cognitive Software-Defined Network (CSDN) combines the efficiencies of SDN with cognitive learning algorithms and enhanced protocols to automatize SDN. Partial deployment of SDN along with traditional networking devices forms a Hybrid Software-Defined Network (HSDN). Software-Defined Network Frameworks: Security Issues and Use Cases consolidates the research relating to the security in SDN, CSDN, and Hybrid SDNs. The security enhancements derived from the use of various SDN frameworks and the security challenges thus introduced, are also discussed. Overall, this book explains the different architectures of SDNs and the security challenges needed for implementing them.

Features:

  • Illustrates different frameworks of SDN and their security issues in a single volume
  • Discusses design and assessment of efficient SDN northbound/southbound interfaces
  • Describes cognitive computing, affective computing, machine learning, and other novel tools
  • Illustrates coupling of SDN and traditional networking – Hybrid SDN
  • Explores services, technologies, algorithms, and methods for data analysis in CSDN

The book is aimed at researchers and graduate students in software engineering, network security, computer networks, high performance computing, communications engineering, and intelligent systems.

This book consolidates the research relating to the security in SDN, CSDN, and Hybrid SDNs. The security enhancements derived from use of various SDN frameworks and the security challenges thus introduced, are also discussed. Overall, this book explains different architectures of SDNs and the security challenges needs for implementing them.

Software-Defined Networks (SDN) work by virtualization of the network and the Cognitive Software-Defined Network (CSDN) combines the efficiencies of SDN with cognitive learning algorithms and enhanced protocols to automatize SDN. Partial deployment of SDN along with traditional networking devices forms a Hybrid Software-Defined Network (HSDN). Software-Defined Network Frameworks: Security Issues and Use Cases consolidates the research relating to the security in SDN, CSDN, and Hybrid SDNs. The security enhancements derived from the use of various SDN frameworks and the security challenges thus introduced, are also discussed. Overall, this book explains the different architectures of SDNs and the security challenges needed for implementing them.

Features:

  • Illustrates different frameworks of SDN and their security issues in a single volume
  • Discusses design and assessment of efficient SDN northbound/southbound interfaces
  • Describes cognitive computing, affective computing, machine learning, and other novel tools
  • Illustrates coupling of SDN and traditional networking – Hybrid SDN
  • Explores services, technologies, algorithms, and methods for data analysis in CSDN

The book is aimed at researchers and graduate students in software engineering, network security, computer networks, high performance computing, communications engineering, and intelligent systems.

This book consolidates the research relating to the security in SDN, CSDN, and Hybrid SDNs. The security enhancements derived from use of various SDN frameworks and the security challenges thus introduced, are also discussed. Overall, this book explains different architectures of SDNs and the security challenges needs for implementing them.

Software-Defined Networks (SDN) work by virtualization of the network and the Cognitive Software-Defined Network (CSDN) combines the efficiencies of SDN with cognitive learning algorithms and enhanced protocols to automatize SDN. Partial deployment of SDN along with traditional networking devices forms a Hybrid Software-Defined Network (HSDN). Software-Defined Network Frameworks: Security Issues and Use Cases consolidates the research relating to the security in SDN, CSDN, and Hybrid SDNs. The security enhancements derived from the use of various SDN frameworks and the security challenges thus introduced, are also discussed. Overall, this book explains the different architectures of SDNs and the security challenges needed for implementing them.

Features:

  • Illustrates different frameworks of SDN and their security issues in a single volume
  • Discusses design and assessment of efficient SDN northbound/southbound interfaces
  • Describes cognitive computing, affective computing, machine learning, and other novel tools
  • Illustrates coupling of SDN and traditional networking – Hybrid SDN
  • Explores services, technologies, algorithms, and methods for data analysis in CSDN

The book is aimed at researchers and graduate students in software engineering, network security, computer networks, high performance computing, communications engineering, and intelligent systems.

This book consolidates the research relating to the security in SDN, CSDN, and Hybrid SDNs. The security enhancements derived from use of various SDN frameworks and the security challenges thus introduced, are also discussed. Overall, this book explains different architectures of SDNs and the security challenges needs for implementing them.

Software-Defined Networks (SDN) work by virtualization of the network and the Cognitive Software-Defined Network (CSDN) combines the efficiencies of SDN with cognitive learning algorithms and enhanced protocols to automatize SDN. Partial deployment of SDN along with traditional networking devices forms a Hybrid Software-Defined Network (HSDN). Software-Defined Network Frameworks: Security Issues and Use Cases consolidates the research relating to the security in SDN, CSDN, and Hybrid SDNs. The security enhancements derived from the use of various SDN frameworks and the security challenges thus introduced, are also discussed. Overall, this book explains the different architectures of SDNs and the security challenges needed for implementing them.

Features:

  • Illustrates different frameworks of SDN and their security issues in a single volume
  • Discusses design and assessment of efficient SDN northbound/southbound interfaces
  • Describes cognitive computing, affective computing, machine learning, and other novel tools
  • Illustrates coupling of SDN and traditional networking – Hybrid SDN
  • Explores services, technologies, algorithms, and methods for data analysis in CSDN

The book is aimed at researchers and graduate students in software engineering, network security, computer networks, high performance computing, communications engineering, and intelligent systems.

This book consolidates the research relating to the security in SDN, CSDN, and Hybrid SDNs. The security enhancements derived from use of various SDN frameworks and the security challenges thus introduced, are also discussed. Overall, this book explains different architectures of SDNs and the security challenges needs for implementing them.

Software-Defined Networks (SDN) work by virtualization of the network and the Cognitive Software-Defined Network (CSDN) combines the efficiencies of SDN with cognitive learning algorithms and enhanced protocols to automatize SDN. Partial deployment of SDN along with traditional networking devices forms a Hybrid Software-Defined Network (HSDN). Software-Defined Network Frameworks: Security Issues and Use Cases consolidates the research relating to the security in SDN, CSDN, and Hybrid SDNs. The security enhancements derived from the use of various SDN frameworks and the security challenges thus introduced, are also discussed. Overall, this book explains the different architectures of SDNs and the security challenges needed for implementing them.

Features:

  • Illustrates different frameworks of SDN and their security issues in a single volume
  • Discusses design and assessment of efficient SDN northbound/southbound interfaces
  • Describes cognitive computing, affective computing, machine learning, and other novel tools
  • Illustrates coupling of SDN and traditional networking – Hybrid SDN
  • Explores services, technologies, algorithms, and methods for data analysis in CSDN

The book is aimed at researchers and graduate students in software engineering, network security, computer networks, high performance computing, communications engineering, and intelligent systems.

This book consolidates the research relating to the security in SDN, CSDN, and Hybrid SDNs. The security enhancements derived from use of various SDN frameworks and the security challenges thus introduced, are also discussed. Overall, this book explains different architectures of SDNs and the security challenges needs for implementing them.

Software-Defined Networks (SDN) work by virtualization of the network and the Cognitive Software-Defined Network (CSDN) combines the efficiencies of SDN with cognitive learning algorithms and enhanced protocols to automatize SDN. Partial deployment of SDN along with traditional networking devices forms a Hybrid Software-Defined Network (HSDN). Software-Defined Network Frameworks: Security Issues and Use Cases consolidates the research relating to the security in SDN, CSDN, and Hybrid SDNs. The security enhancements derived from the use of various SDN frameworks and the security challenges thus introduced, are also discussed. Overall, this book explains the different architectures of SDNs and the security challenges needed for implementing them.

Features:

  • Illustrates different frameworks of SDN and their security issues in a single volume
  • Discusses design and assessment of efficient SDN northbound/southbound interfaces
  • Describes cognitive computing, affective computing, machine learning, and other novel tools
  • Illustrates coupling of SDN and traditional networking – Hybrid SDN
  • Explores services, technologies, algorithms, and methods for data analysis in CSDN

The book is aimed at researchers and graduate students in software engineering, network security, computer networks, high performance computing, communications engineering, and intelligent systems.

This book consolidates the research relating to the security in SDN, CSDN, and Hybrid SDNs. The security enhancements derived from use of various SDN frameworks and the security challenges thus introduced, are also discussed. Overall, this book explains different architectures of SDNs and the security challenges needs for implementing them.

Software-Defined Networks (SDN) work by virtualization of the network and the Cognitive Software-Defined Network (CSDN) combines the efficiencies of SDN with cognitive learning algorithms and enhanced protocols to automatize SDN. Partial deployment of SDN along with traditional networking devices forms a Hybrid Software-Defined Network (HSDN). Software-Defined Network Frameworks: Security Issues and Use Cases consolidates the research relating to the security in SDN, CSDN, and Hybrid SDNs. The security enhancements derived from the use of various SDN frameworks and the security challenges thus introduced, are also discussed. Overall, this book explains the different architectures of SDNs and the security challenges needed for implementing them.

Features:

  • Illustrates different frameworks of SDN and their security issues in a single volume
  • Discusses design and assessment of efficient SDN northbound/southbound interfaces
  • Describes cognitive computing, affective computing, machine learning, and other novel tools
  • Illustrates coupling of SDN and traditional networking – Hybrid SDN
  • Explores services, technologies, algorithms, and methods for data analysis in CSDN

The book is aimed at researchers and graduate students in software engineering, network security, computer networks, high performance computing, communications engineering, and intelligent systems.

This book consolidates the research relating to the security in SDN, CSDN, and Hybrid SDNs. The security enhancements derived from use of various SDN frameworks and the security challenges thus introduced, are also discussed. Overall, this book explains different architectures of SDNs and the security challenges needs for implementing them.

Software-Defined Networks (SDN) work by virtualization of the network and the Cognitive Software-Defined Network (CSDN) combines the efficiencies of SDN with cognitive learning algorithms and enhanced protocols to automatize SDN. Partial deployment of SDN along with traditional networking devices forms a Hybrid Software-Defined Network (HSDN). Software-Defined Network Frameworks: Security Issues and Use Cases consolidates the research relating to the security in SDN, CSDN, and Hybrid SDNs. The security enhancements derived from the use of various SDN frameworks and the security challenges thus introduced, are also discussed. Overall, this book explains the different architectures of SDNs and the security challenges needed for implementing them.

Features:

  • Illustrates different frameworks of SDN and their security issues in a single volume
  • Discusses design and assessment of efficient SDN northbound/southbound interfaces
  • Describes cognitive computing, affective computing, machine learning, and other novel tools
  • Illustrates coupling of SDN and traditional networking – Hybrid SDN
  • Explores services, technologies, algorithms, and methods for data analysis in CSDN

The book is aimed at researchers and graduate students in software engineering, network security, computer networks, high performance computing, communications engineering, and intelligent systems.

This book consolidates the research relating to the security in SDN, CSDN, and Hybrid SDNs. The security enhancements derived from use of various SDN frameworks and the security challenges thus introduced, are also discussed. Overall, this book explains different architectures of SDNs and the security challenges needs for implementing them.

Software-Defined Networks (SDN) work by virtualization of the network and the Cognitive Software-Defined Network (CSDN) combines the efficiencies of SDN with cognitive learning algorithms and enhanced protocols to automatize SDN. Partial deployment of SDN along with traditional networking devices forms a Hybrid Software-Defined Network (HSDN). Software-Defined Network Frameworks: Security Issues and Use Cases consolidates the research relating to the security in SDN, CSDN, and Hybrid SDNs. The security enhancements derived from the use of various SDN frameworks and the security challenges thus introduced, are also discussed. Overall, this book explains the different architectures of SDNs and the security challenges needed for implementing them.

Features:

  • Illustrates different frameworks of SDN and their security issues in a single volume
  • Discusses design and assessment of efficient SDN northbound/southbound interfaces
  • Describes cognitive computing, affective computing, machine learning, and other novel tools
  • Illustrates coupling of SDN and traditional networking – Hybrid SDN
  • Explores services, technologies, algorithms, and methods for data analysis in CSDN

The book is aimed at researchers and graduate students in software engineering, network security, computer networks, high performance computing, communications engineering, and intelligent systems.

This book consolidates the research relating to the security in SDN, CSDN, and Hybrid SDNs. The security enhancements derived from use of various SDN frameworks and the security challenges thus introduced, are also discussed. Overall, this book explains different architectures of SDNs and the security challenges needs for implementing them.

Software-Defined Networks (SDN) work by virtualization of the network and the Cognitive Software-Defined Network (CSDN) combines the efficiencies of SDN with cognitive learning algorithms and enhanced protocols to automatize SDN. Partial deployment of SDN along with traditional networking devices forms a Hybrid Software-Defined Network (HSDN). Software-Defined Network Frameworks: Security Issues and Use Cases consolidates the research relating to the security in SDN, CSDN, and Hybrid SDNs. The security enhancements derived from the use of various SDN frameworks and the security challenges thus introduced, are also discussed. Overall, this book explains the different architectures of SDNs and the security challenges needed for implementing them.

Features:

  • Illustrates different frameworks of SDN and their security issues in a single volume
  • Discusses design and assessment of efficient SDN northbound/southbound interfaces
  • Describes cognitive computing, affective computing, machine learning, and other novel tools
  • Illustrates coupling of SDN and traditional networking – Hybrid SDN
  • Explores services, technologies, algorithms, and methods for data analysis in CSDN

The book is aimed at researchers and graduate students in software engineering, network security, computer networks, high performance computing, communications engineering, and intelligent systems.

This book consolidates the research relating to the security in SDN, CSDN, and Hybrid SDNs. The security enhancements derived from use of various SDN frameworks and the security challenges thus introduced, are also discussed. Overall, this book explains different architectures of SDNs and the security challenges needs for implementing them.

Software-Defined Networks (SDN) work by virtualization of the network and the Cognitive Software-Defined Network (CSDN) combines the efficiencies of SDN with cognitive learning algorithms and enhanced protocols to automatize SDN. Partial deployment of SDN along with traditional networking devices forms a Hybrid Software-Defined Network (HSDN). Software-Defined Network Frameworks: Security Issues and Use Cases consolidates the research relating to the security in SDN, CSDN, and Hybrid SDNs. The security enhancements derived from the use of various SDN frameworks and the security challenges thus introduced, are also discussed. Overall, this book explains the different architectures of SDNs and the security challenges needed for implementing them.

Features:

  • Illustrates different frameworks of SDN and their security issues in a single volume
  • Discusses design and assessment of efficient SDN northbound/southbound interfaces
  • Describes cognitive computing, affective computing, machine learning, and other novel tools
  • Illustrates coupling of SDN and traditional networking – Hybrid SDN
  • Explores services, technologies, algorithms, and methods for data analysis in CSDN

The book is aimed at researchers and graduate students in software engineering, network security, computer networks, high performance computing, communications engineering, and intelligent systems.

This book consolidates the research relating to the security in SDN, CSDN, and Hybrid SDNs. The security enhancements derived from use of various SDN frameworks and the security challenges thus introduced, are also discussed. Overall, this book explains different architectures of SDNs and the security challenges needs for implementing them.

Software-Defined Networks (SDN) work by virtualization of the network and the Cognitive Software-Defined Network (CSDN) combines the efficiencies of SDN with cognitive learning algorithms and enhanced protocols to automatize SDN. Partial deployment of SDN along with traditional networking devices forms a Hybrid Software-Defined Network (HSDN). Software-Defined Network Frameworks: Security Issues and Use Cases consolidates the research relating to the security in SDN, CSDN, and Hybrid SDNs. The security enhancements derived from the use of various SDN frameworks and the security challenges thus introduced, are also discussed. Overall, this book explains the different architectures of SDNs and the security challenges needed for implementing them.

Features:

  • Illustrates different frameworks of SDN and their security issues in a single volume
  • Discusses design and assessment of efficient SDN northbound/southbound interfaces
  • Describes cognitive computing, affective computing, machine learning, and other novel tools
  • Illustrates coupling of SDN and traditional networking – Hybrid SDN
  • Explores services, technologies, algorithms, and methods for data analysis in CSDN

The book is aimed at researchers and graduate students in software engineering, network security, computer networks, high performance computing, communications engineering, and intelligent systems.

This book consolidates the research relating to the security in SDN, CSDN, and Hybrid SDNs. The security enhancements derived from use of various SDN frameworks and the security challenges thus introduced, are also discussed. Overall, this book explains different architectures of SDNs and the security challenges needs for implementing them.

Software-Defined Networks (SDN) work by virtualization of the network and the Cognitive Software-Defined Network (CSDN) combines the efficiencies of SDN with cognitive learning algorithms and enhanced protocols to automatize SDN. Partial deployment of SDN along with traditional networking devices forms a Hybrid Software-Defined Network (HSDN). Software-Defined Network Frameworks: Security Issues and Use Cases consolidates the research relating to the security in SDN, CSDN, and Hybrid SDNs. The security enhancements derived from the use of various SDN frameworks and the security challenges thus introduced, are also discussed. Overall, this book explains the different architectures of SDNs and the security challenges needed for implementing them.

Features:

  • Illustrates different frameworks of SDN and their security issues in a single volume
  • Discusses design and assessment of efficient SDN northbound/southbound interfaces
  • Describes cognitive computing, affective computing, machine learning, and other novel tools
  • Illustrates coupling of SDN and traditional networking – Hybrid SDN
  • Explores services, technologies, algorithms, and methods for data analysis in CSDN

The book is aimed at researchers and graduate students in software engineering, network security, computer networks, high performance computing, communications engineering, and intelligent systems.

This book consolidates the research relating to the security in SDN, CSDN, and Hybrid SDNs. The security enhancements derived from use of various SDN frameworks and the security challenges thus introduced, are also discussed. Overall, this book explains different architectures of SDNs and the security challenges needs for implementing them.

Software-Defined Networks (SDN) work by virtualization of the network and the Cognitive Software-Defined Network (CSDN) combines the efficiencies of SDN with cognitive learning algorithms and enhanced protocols to automatize SDN. Partial deployment of SDN along with traditional networking devices forms a Hybrid Software-Defined Network (HSDN). Software-Defined Network Frameworks: Security Issues and Use Cases consolidates the research relating to the security in SDN, CSDN, and Hybrid SDNs. The security enhancements derived from the use of various SDN frameworks and the security challenges thus introduced, are also discussed. Overall, this book explains the different architectures of SDNs and the security challenges needed for implementing them.

Features:

  • Illustrates different frameworks of SDN and their security issues in a single volume
  • Discusses design and assessment of efficient SDN northbound/southbound interfaces
  • Describes cognitive computing, affective computing, machine learning, and other novel tools
  • Illustrates coupling of SDN and traditional networking – Hybrid SDN
  • Explores services, technologies, algorithms, and methods for data analysis in CSDN

The book is aimed at researchers and graduate students in software engineering, network security, computer networks, high performance computing, communications engineering, and intelligent systems.

This book consolidates the research relating to the security in SDN, CSDN, and Hybrid SDNs. The security enhancements derived from use of various SDN frameworks and the security challenges thus introduced, are also discussed. Overall, this book explains different architectures of SDNs and the security challenges needs for implementing them.

Software-Defined Networks (SDN) work by virtualization of the network and the Cognitive Software-Defined Network (CSDN) combines the efficiencies of SDN with cognitive learning algorithms and enhanced protocols to automatize SDN. Partial deployment of SDN along with traditional networking devices forms a Hybrid Software-Defined Network (HSDN). Software-Defined Network Frameworks: Security Issues and Use Cases consolidates the research relating to the security in SDN, CSDN, and Hybrid SDNs. The security enhancements derived from the use of various SDN frameworks and the security challenges thus introduced, are also discussed. Overall, this book explains the different architectures of SDNs and the security challenges needed for implementing them.

Features:

  • Illustrates different frameworks of SDN and their security issues in a single volume
  • Discusses design and assessment of efficient SDN northbound/southbound interfaces
  • Describes cognitive computing, affective computing, machine learning, and other novel tools
  • Illustrates coupling of SDN and traditional networking – Hybrid SDN
  • Explores services, technologies, algorithms, and methods for data analysis in CSDN

The book is aimed at researchers and graduate students in software engineering, network security, computer networks, high performance computing, communications engineering, and intelligent systems.

This book consolidates the research relating to the security in SDN, CSDN, and Hybrid SDNs. The security enhancements derived from use of various SDN frameworks and the security challenges thus introduced, are also discussed. Overall, this book explains different architectures of SDNs and the security challenges needs for implementing them.

Software-Defined Networks (SDN) work by virtualization of the network and the Cognitive Software-Defined Network (CSDN) combines the efficiencies of SDN with cognitive learning algorithms and enhanced protocols to automatize SDN. Partial deployment of SDN along with traditional networking devices forms a Hybrid Software-Defined Network (HSDN). Software-Defined Network Frameworks: Security Issues and Use Cases consolidates the research relating to the security in SDN, CSDN, and Hybrid SDNs. The security enhancements derived from the use of various SDN frameworks and the security challenges thus introduced, are also discussed. Overall, this book explains the different architectures of SDNs and the security challenges needed for implementing them.

Features:

  • Illustrates different frameworks of SDN and their security issues in a single volume
  • Discusses design and assessment of efficient SDN northbound/southbound interfaces
  • Describes cognitive computing, affective computing, machine learning, and other novel tools
  • Illustrates coupling of SDN and traditional networking – Hybrid SDN
  • Explores services, technologies, algorithms, and methods for data analysis in CSDN

The book is aimed at researchers and graduate students in software engineering, network security, computer networks, high performance computing, communications engineering, and intelligent systems.

This book consolidates the research relating to the security in SDN, CSDN, and Hybrid SDNs. The security enhancements derived from use of various SDN frameworks and the security challenges thus introduced, are also discussed. Overall, this book explains different architectures of SDNs and the security challenges needs for implementing them.

Software-Defined Networks (SDN) work by virtualization of the network and the Cognitive Software-Defined Network (CSDN) combines the efficiencies of SDN with cognitive learning algorithms and enhanced protocols to automatize SDN. Partial deployment of SDN along with traditional networking devices forms a Hybrid Software-Defined Network (HSDN). Software-Defined Network Frameworks: Security Issues and Use Cases consolidates the research relating to the security in SDN, CSDN, and Hybrid SDNs. The security enhancements derived from the use of various SDN frameworks and the security challenges thus introduced, are also discussed. Overall, this book explains the different architectures of SDNs and the security challenges needed for implementing them.

Features:

  • Illustrates different frameworks of SDN and their security issues in a single volume
  • Discusses design and assessment of efficient SDN northbound/southbound interfaces
  • Describes cognitive computing, affective computing, machine learning, and other novel tools
  • Illustrates coupling of SDN and traditional networking – Hybrid SDN
  • Explores services, technologies, algorithms, and methods for data analysis in CSDN

The book is aimed at researchers and graduate students in software engineering, network security, computer networks, high performance computing, communications engineering, and intelligent systems.

This book consolidates the research relating to the security in SDN, CSDN, and Hybrid SDNs. The security enhancements derived from use of various SDN frameworks and the security challenges thus introduced, are also discussed. Overall, this book explains different architectures of SDNs and the security challenges needs for implementing them.

Software-Defined Networks (SDN) work by virtualization of the network and the Cognitive Software-Defined Network (CSDN) combines the efficiencies of SDN with cognitive learning algorithms and enhanced protocols to automatize SDN. Partial deployment of SDN along with traditional networking devices forms a Hybrid Software-Defined Network (HSDN). Software-Defined Network Frameworks: Security Issues and Use Cases consolidates the research relating to the security in SDN, CSDN, and Hybrid SDNs. The security enhancements derived from the use of various SDN frameworks and the security challenges thus introduced, are also discussed. Overall, this book explains the different architectures of SDNs and the security challenges needed for implementing them.

Features:

  • Illustrates different frameworks of SDN and their security issues in a single volume
  • Discusses design and assessment of efficient SDN northbound/southbound interfaces
  • Describes cognitive computing, affective computing, machine learning, and other novel tools
  • Illustrates coupling of SDN and traditional networking – Hybrid SDN
  • Explores services, technologies, algorithms, and methods for data analysis in CSDN

The book is aimed at researchers and graduate students in software engineering, network security, computer networks, high performance computing, communications engineering, and intelligent systems.

This book consolidates the research relating to the security in SDN, CSDN, and Hybrid SDNs. The security enhancements derived from use of various SDN frameworks and the security challenges thus introduced, are also discussed. Overall, this book explains different architectures of SDNs and the security challenges needs for implementing them.

Software-Defined Networks (SDN) work by virtualization of the network and the Cognitive Software-Defined Network (CSDN) combines the efficiencies of SDN with cognitive learning algorithms and enhanced protocols to automatize SDN. Partial deployment of SDN along with traditional networking devices forms a Hybrid Software-Defined Network (HSDN). Software-Defined Network Frameworks: Security Issues and Use Cases consolidates the research relating to the security in SDN, CSDN, and Hybrid SDNs. The security enhancements derived from the use of various SDN frameworks and the security challenges thus introduced, are also discussed. Overall, this book explains the different architectures of SDNs and the security challenges needed for implementing them.

Features:

  • Illustrates different frameworks of SDN and their security issues in a single volume
  • Discusses design and assessment of efficient SDN northbound/southbound interfaces
  • Describes cognitive computing, affective computing, machine learning, and other novel tools
  • Illustrates coupling of SDN and traditional networking – Hybrid SDN
  • Explores services, technologies, algorithms, and methods for data analysis in CSDN

The book is aimed at researchers and graduate students in software engineering, network security, computer networks, high performance computing, communications engineering, and intelligent systems.

This book consolidates the research relating to the security in SDN, CSDN, and Hybrid SDNs. The security enhancements derived from use of various SDN frameworks and the security challenges thus introduced, are also discussed. Overall, this book explains different architectures of SDNs and the security challenges needs for implementing them.

Software-Defined Networks (SDN) work by virtualization of the network and the Cognitive Software-Defined Network (CSDN) combines the efficiencies of SDN with cognitive learning algorithms and enhanced protocols to automatize SDN. Partial deployment of SDN along with traditional networking devices forms a Hybrid Software-Defined Network (HSDN). Software-Defined Network Frameworks: Security Issues and Use Cases consolidates the research relating to the security in SDN, CSDN, and Hybrid SDNs. The security enhancements derived from the use of various SDN frameworks and the security challenges thus introduced, are also discussed. Overall, this book explains the different architectures of SDNs and the security challenges needed for implementing them.

Features:

  • Illustrates different frameworks of SDN and their security issues in a single volume
  • Discusses design and assessment of efficient SDN northbound/southbound interfaces
  • Describes cognitive computing, affective computing, machine learning, and other novel tools
  • Illustrates coupling of SDN and traditional networking – Hybrid SDN
  • Explores services, technologies, algorithms, and methods for data analysis in CSDN

The book is aimed at researchers and graduate students in software engineering, network security, computer networks, high performance computing, communications engineering, and intelligent systems.

This book consolidates the research relating to the security in SDN, CSDN, and Hybrid SDNs. The security enhancements derived from use of various SDN frameworks and the security challenges thus introduced, are also discussed. Overall, this book explains different architectures of SDNs and the security challenges needs for implementing them.

Software-Defined Networks (SDN) work by virtualization of the network and the Cognitive Software-Defined Network (CSDN) combines the efficiencies of SDN with cognitive learning algorithms and enhanced protocols to automatize SDN. Partial deployment of SDN along with traditional networking devices forms a Hybrid Software-Defined Network (HSDN). Software-Defined Network Frameworks: Security Issues and Use Cases consolidates the research relating to the security in SDN, CSDN, and Hybrid SDNs. The security enhancements derived from the use of various SDN frameworks and the security challenges thus introduced, are also discussed. Overall, this book explains the different architectures of SDNs and the security challenges needed for implementing them.

Features:

  • Illustrates different frameworks of SDN and their security issues in a single volume
  • Discusses design and assessment of efficient SDN northbound/southbound interfaces
  • Describes cognitive computing, affective computing, machine learning, and other novel tools
  • Illustrates coupling of SDN and traditional networking – Hybrid SDN
  • Explores services, technologies, algorithms, and methods for data analysis in CSDN

The book is aimed at researchers and graduate students in software engineering, network security, computer networks, high performance computing, communications engineering, and intelligent systems.

This book consolidates the research relating to the security in SDN, CSDN, and Hybrid SDNs. The security enhancements derived from use of various SDN frameworks and the security challenges thus introduced, are also discussed. Overall, this book explains different architectures of SDNs and the security challenges needs for implementing them.

Software-Defined Networks (SDN) work by virtualization of the network and the Cognitive Software-Defined Network (CSDN) combines the efficiencies of SDN with cognitive learning algorithms and enhanced protocols to automatize SDN. Partial deployment of SDN along with traditional networking devices forms a Hybrid Software-Defined Network (HSDN). Software-Defined Network Frameworks: Security Issues and Use Cases consolidates the research relating to the security in SDN, CSDN, and Hybrid SDNs. The security enhancements derived from the use of various SDN frameworks and the security challenges thus introduced, are also discussed. Overall, this book explains the different architectures of SDNs and the security challenges needed for implementing them.

Features:

  • Illustrates different frameworks of SDN and their security issues in a single volume
  • Discusses design and assessment of efficient SDN northbound/southbound interfaces
  • Describes cognitive computing, affective computing, machine learning, and other novel tools
  • Illustrates coupling of SDN and traditional networking – Hybrid SDN
  • Explores services, technologies, algorithms, and methods for data analysis in CSDN

The book is aimed at researchers and graduate students in software engineering, network security, computer networks, high performance computing, communications engineering, and intelligent systems.

This book consolidates the research relating to the security in SDN, CSDN, and Hybrid SDNs. The security enhancements derived from use of various SDN frameworks and the security challenges thus introduced, are also discussed. Overall, this book explains different architectures of SDNs and the security challenges needs for implementing them.

Software-Defined Networks (SDN) work by virtualization of the network and the Cognitive Software-Defined Network (CSDN) combines the efficiencies of SDN with cognitive learning algorithms and enhanced protocols to automatize SDN. Partial deployment of SDN along with traditional networking devices forms a Hybrid Software-Defined Network (HSDN). Software-Defined Network Frameworks: Security Issues and Use Cases consolidates the research relating to the security in SDN, CSDN, and Hybrid SDNs. The security enhancements derived from the use of various SDN frameworks and the security challenges thus introduced, are also discussed. Overall, this book explains the different architectures of SDNs and the security challenges needed for implementing them.

Features:

  • Illustrates different frameworks of SDN and their security issues in a single volume
  • Discusses design and assessment of efficient SDN northbound/southbound interfaces
  • Describes cognitive computing, affective computing, machine learning, and other novel tools
  • Illustrates coupling of SDN and traditional networking – Hybrid SDN
  • Explores services, technologies, algorithms, and methods for data analysis in CSDN

The book is aimed at researchers and graduate students in software engineering, network security, computer networks, high performance computing, communications engineering, and intelligent systems.

This book consolidates the research relating to the security in SDN, CSDN, and Hybrid SDNs. The security enhancements derived from use of various SDN frameworks and the security challenges thus introduced, are also discussed. Overall, this book explains different architectures of SDNs and the security challenges needs for implementing them.

Software-Defined Networks (SDN) work by virtualization of the network and the Cognitive Software-Defined Network (CSDN) combines the efficiencies of SDN with cognitive learning algorithms and enhanced protocols to automatize SDN. Partial deployment of SDN along with traditional networking devices forms a Hybrid Software-Defined Network (HSDN). Software-Defined Network Frameworks: Security Issues and Use Cases consolidates the research relating to the security in SDN, CSDN, and Hybrid SDNs. The security enhancements derived from the use of various SDN frameworks and the security challenges thus introduced, are also discussed. Overall, this book explains the different architectures of SDNs and the security challenges needed for implementing them.

Features:

  • Illustrates different frameworks of SDN and their security issues in a single volume
  • Discusses design and assessment of efficient SDN northbound/southbound interfaces
  • Describes cognitive computing, affective computing, machine learning, and other novel tools
  • Illustrates coupling of SDN and traditional networking – Hybrid SDN
  • Explores services, technologies, algorithms, and methods for data analysis in CSDN

The book is aimed at researchers and graduate students in software engineering, network security, computer networks, high performance computing, communications engineering, and intelligent systems.

This book consolidates the research relating to the security in SDN, CSDN, and Hybrid SDNs. The security enhancements derived from use of various SDN frameworks and the security challenges thus introduced, are also discussed. Overall, this book explains different architectures of SDNs and the security challenges needs for implementing them.

Software-Defined Networks (SDN) work by virtualization of the network and the Cognitive Software-Defined Network (CSDN) combines the efficiencies of SDN with cognitive learning algorithms and enhanced protocols to automatize SDN. Partial deployment of SDN along with traditional networking devices forms a Hybrid Software-Defined Network (HSDN). Software-Defined Network Frameworks: Security Issues and Use Cases consolidates the research relating to the security in SDN, CSDN, and Hybrid SDNs. The security enhancements derived from the use of various SDN frameworks and the security challenges thus introduced, are also discussed. Overall, this book explains the different architectures of SDNs and the security challenges needed for implementing them.

Features:

  • Illustrates different frameworks of SDN and their security issues in a single volume
  • Discusses design and assessment of efficient SDN northbound/southbound interfaces
  • Describes cognitive computing, affective computing, machine learning, and other novel tools
  • Illustrates coupling of SDN and traditional networking – Hybrid SDN
  • Explores services, technologies, algorithms, and methods for data analysis in CSDN

The book is aimed at researchers and graduate students in software engineering, network security, computer networks, high performance computing, communications engineering, and intelligent systems.

This book consolidates the research relating to the security in SDN, CSDN, and Hybrid SDNs. The security enhancements derived from use of various SDN frameworks and the security challenges thus introduced, are also discussed. Overall, this book explains different architectures of SDNs and the security challenges needs for implementing them.

Software-Defined Networks (SDN) work by virtualization of the network and the Cognitive Software-Defined Network (CSDN) combines the efficiencies of SDN with cognitive learning algorithms and enhanced protocols to automatize SDN. Partial deployment of SDN along with traditional networking devices forms a Hybrid Software-Defined Network (HSDN). Software-Defined Network Frameworks: Security Issues and Use Cases consolidates the research relating to the security in SDN, CSDN, and Hybrid SDNs. The security enhancements derived from the use of various SDN frameworks and the security challenges thus introduced, are also discussed. Overall, this book explains the different architectures of SDNs and the security challenges needed for implementing them.

Features:

  • Illustrates different frameworks of SDN and their security issues in a single volume
  • Discusses design and assessment of efficient SDN northbound/southbound interfaces
  • Describes cognitive computing, affective computing, machine learning, and other novel tools
  • Illustrates coupling of SDN and traditional networking – Hybrid SDN
  • Explores services, technologies, algorithms, and methods for data analysis in CSDN

The book is aimed at researchers and graduate students in software engineering, network security, computer networks, high performance computing, communications engineering, and intelligent systems.

This book consolidates the research relating to the security in SDN, CSDN, and Hybrid SDNs. The security enhancements derived from use of various SDN frameworks and the security challenges thus introduced, are also discussed. Overall, this book explains different architectures of SDNs and the security challenges needs for implementing them.

Software-Defined Networks (SDN) work by virtualization of the network and the Cognitive Software-Defined Network (CSDN) combines the efficiencies of SDN with cognitive learning algorithms and enhanced protocols to automatize SDN. Partial deployment of SDN along with traditional networking devices forms a Hybrid Software-Defined Network (HSDN). Software-Defined Network Frameworks: Security Issues and Use Cases consolidates the research relating to the security in SDN, CSDN, and Hybrid SDNs. The security enhancements derived from the use of various SDN frameworks and the security challenges thus introduced, are also discussed. Overall, this book explains the different architectures of SDNs and the security challenges needed for implementing them.

Features:

  • Illustrates different frameworks of SDN and their security issues in a single volume
  • Discusses design and assessment of efficient SDN northbound/southbound interfaces
  • Describes cognitive computing, affective computing, machine learning, and other novel tools
  • Illustrates coupling of SDN and traditional networking – Hybrid SDN
  • Explores services, technologies, algorithms, and methods for data analysis in CSDN

The book is aimed at researchers and graduate students in software engineering, network security, computer networks, high performance computing, communications engineering, and intelligent systems.

This book consolidates the research relating to the security in SDN, CSDN, and Hybrid SDNs. The security enhancements derived from use of various SDN frameworks and the security challenges thus introduced, are also discussed. Overall, this book explains different architectures of SDNs and the security challenges needs for implementing them.

Software-Defined Networks (SDN) work by virtualization of the network and the Cognitive Software-Defined Network (CSDN) combines the efficiencies of SDN with cognitive learning algorithms and enhanced protocols to automatize SDN. Partial deployment of SDN along with traditional networking devices forms a Hybrid Software-Defined Network (HSDN). Software-Defined Network Frameworks: Security Issues and Use Cases consolidates the research relating to the security in SDN, CSDN, and Hybrid SDNs. The security enhancements derived from the use of various SDN frameworks and the security challenges thus introduced, are also discussed. Overall, this book explains the different architectures of SDNs and the security challenges needed for implementing them.

Features:

  • Illustrates different frameworks of SDN and their security issues in a single volume
  • Discusses design and assessment of efficient SDN northbound/southbound interfaces
  • Describes cognitive computing, affective computing, machine learning, and other novel tools
  • Illustrates coupling of SDN and traditional networking – Hybrid SDN
  • Explores services, technologies, algorithms, and methods for data analysis in CSDN

The book is aimed at researchers and graduate students in software engineering, network security, computer networks, high performance computing, communications engineering, and intelligent systems.

This book consolidates the research relating to the security in SDN, CSDN, and Hybrid SDNs. The security enhancements derived from use of various SDN frameworks and the security challenges thus introduced, are also discussed. Overall, this book explains different architectures of SDNs and the security challenges needs for implementing them.

Software-Defined Networks (SDN) work by virtualization of the network and the Cognitive Software-Defined Network (CSDN) combines the efficiencies of SDN with cognitive learning algorithms and enhanced protocols to automatize SDN. Partial deployment of SDN along with traditional networking devices forms a Hybrid Software-Defined Network (HSDN). Software-Defined Network Frameworks: Security Issues and Use Cases consolidates the research relating to the security in SDN, CSDN, and Hybrid SDNs. The security enhancements derived from the use of various SDN frameworks and the security challenges thus introduced, are also discussed. Overall, this book explains the different architectures of SDNs and the security challenges needed for implementing them.

Features:

  • Illustrates different frameworks of SDN and their security issues in a single volume
  • Discusses design and assessment of efficient SDN northbound/southbound interfaces
  • Describes cognitive computing, affective computing, machine learning, and other novel tools
  • Illustrates coupling of SDN and traditional networking – Hybrid SDN
  • Explores services, technologies, algorithms, and methods for data analysis in CSDN

The book is aimed at researchers and graduate students in software engineering, network security, computer networks, high performance computing, communications engineering, and intelligent systems.

This book consolidates the research relating to the security in SDN, CSDN, and Hybrid SDNs. The security enhancements derived from use of various SDN frameworks and the security challenges thus introduced, are also discussed. Overall, this book explains different architectures of SDNs and the security challenges needs for implementing them.

Software-Defined Networks (SDN) work by virtualization of the network and the Cognitive Software-Defined Network (CSDN) combines the efficiencies of SDN with cognitive learning algorithms and enhanced protocols to automatize SDN. Partial deployment of SDN along with traditional networking devices forms a Hybrid Software-Defined Network (HSDN). Software-Defined Network Frameworks: Security Issues and Use Cases consolidates the research relating to the security in SDN, CSDN, and Hybrid SDNs. The security enhancements derived from the use of various SDN frameworks and the security challenges thus introduced, are also discussed. Overall, this book explains the different architectures of SDNs and the security challenges needed for implementing them.

Features:

  • Illustrates different frameworks of SDN and their security issues in a single volume
  • Discusses design and assessment of efficient SDN northbound/southbound interfaces
  • Describes cognitive computing, affective computing, machine learning, and other novel tools
  • Illustrates coupling of SDN and traditional networking – Hybrid SDN
  • Explores services, technologies, algorithms, and methods for data analysis in CSDN

The book is aimed at researchers and graduate students in software engineering, network security, computer networks, high performance computing, communications engineering, and intelligent systems.

This book consolidates the research relating to the security in SDN, CSDN, and Hybrid SDNs. The security enhancements derived from use of various SDN frameworks and the security challenges thus introduced, are also discussed. Overall, this book explains different architectures of SDNs and the security challenges needs for implementing them.

Software-Defined Networks (SDN) work by virtualization of the network and the Cognitive Software-Defined Network (CSDN) combines the efficiencies of SDN with cognitive learning algorithms and enhanced protocols to automatize SDN. Partial deployment of SDN along with traditional networking devices forms a Hybrid Software-Defined Network (HSDN). Software-Defined Network Frameworks: Security Issues and Use Cases consolidates the research relating to the security in SDN, CSDN, and Hybrid SDNs. The security enhancements derived from the use of various SDN frameworks and the security challenges thus introduced, are also discussed. Overall, this book explains the different architectures of SDNs and the security challenges needed for implementing them.

Features:

  • Illustrates different frameworks of SDN and their security issues in a single volume
  • Discusses design and assessment of efficient SDN northbound/southbound interfaces
  • Describes cognitive computing, affective computing, machine learning, and other novel tools
  • Illustrates coupling of SDN and traditional networking – Hybrid SDN
  • Explores services, technologies, algorithms, and methods for data analysis in CSDN

The book is aimed at researchers and graduate students in software engineering, network security, computer networks, high performance computing, communications engineering, and intelligent systems.

This book consolidates the research relating to the security in SDN, CSDN, and Hybrid SDNs. The security enhancements derived from use of various SDN frameworks and the security challenges thus introduced, are also discussed. Overall, this book explains different architectures of SDNs and the security challenges needs for implementing them.

Software-Defined Networks (SDN) work by virtualization of the network and the Cognitive Software-Defined Network (CSDN) combines the efficiencies of SDN with cognitive learning algorithms and enhanced protocols to automatize SDN. Partial deployment of SDN along with traditional networking devices forms a Hybrid Software-Defined Network (HSDN). Software-Defined Network Frameworks: Security Issues and Use Cases consolidates the research relating to the security in SDN, CSDN, and Hybrid SDNs. The security enhancements derived from the use of various SDN frameworks and the security challenges thus introduced, are also discussed. Overall, this book explains the different architectures of SDNs and the security challenges needed for implementing them.

Features:

  • Illustrates different frameworks of SDN and their security issues in a single volume
  • Discusses design and assessment of efficient SDN northbound/southbound interfaces
  • Describes cognitive computing, affective computing, machine learning, and other novel tools
  • Illustrates coupling of SDN and traditional networking – Hybrid SDN
  • Explores services, technologies, algorithms, and methods for data analysis in CSDN

The book is aimed at researchers and graduate students in software engineering, network security, computer networks, high performance computing, communications engineering, and intelligent systems.

This book consolidates the research relating to the security in SDN, CSDN, and Hybrid SDNs. The security enhancements derived from use of various SDN frameworks and the security challenges thus introduced, are also discussed. Overall, this book explains different architectures of SDNs and the security challenges needs for implementing them.

Software-Defined Networks (SDN) work by virtualization of the network and the Cognitive Software-Defined Network (CSDN) combines the efficiencies of SDN with cognitive learning algorithms and enhanced protocols to automatize SDN. Partial deployment of SDN along with traditional networking devices forms a Hybrid Software-Defined Network (HSDN). Software-Defined Network Frameworks: Security Issues and Use Cases consolidates the research relating to the security in SDN, CSDN, and Hybrid SDNs. The security enhancements derived from the use of various SDN frameworks and the security challenges thus introduced, are also discussed. Overall, this book explains the different architectures of SDNs and the security challenges needed for implementing them.

Features:

  • Illustrates different frameworks of SDN and their security issues in a single volume
  • Discusses design and assessment of efficient SDN northbound/southbound interfaces
  • Describes cognitive computing, affective computing, machine learning, and other novel tools
  • Illustrates coupling of SDN and traditional networking – Hybrid SDN
  • Explores services, technologies, algorithms, and methods for data analysis in CSDN

The book is aimed at researchers and graduate students in software engineering, network security, computer networks, high performance computing, communications engineering, and intelligent systems.

This book consolidates the research relating to the security in SDN, CSDN, and Hybrid SDNs. The security enhancements derived from use of various SDN frameworks and the security challenges thus introduced, are also discussed. Overall, this book explains different architectures of SDNs and the security challenges needs for implementing them.

Software-Defined Networks (SDN) work by virtualization of the network and the Cognitive Software-Defined Network (CSDN) combines the efficiencies of SDN with cognitive learning algorithms and enhanced protocols to automatize SDN. Partial deployment of SDN along with traditional networking devices forms a Hybrid Software-Defined Network (HSDN). Software-Defined Network Frameworks: Security Issues and Use Cases consolidates the research relating to the security in SDN, CSDN, and Hybrid SDNs. The security enhancements derived from the use of various SDN frameworks and the security challenges thus introduced, are also discussed. Overall, this book explains the different architectures of SDNs and the security challenges needed for implementing them.

Features:

  • Illustrates different frameworks of SDN and their security issues in a single volume
  • Discusses design and assessment of efficient SDN northbound/southbound interfaces
  • Describes cognitive computing, affective computing, machine learning, and other novel tools
  • Illustrates coupling of SDN and traditional networking – Hybrid SDN
  • Explores services, technologies, algorithms, and methods for data analysis in CSDN

The book is aimed at researchers and graduate students in software engineering, network security, computer networks, high performance computing, communications engineering, and intelligent systems.

This book consolidates the research relating to the security in SDN, CSDN, and Hybrid SDNs. The security enhancements derived from use of various SDN frameworks and the security challenges thus introduced, are also discussed. Overall, this book explains different architectures of SDNs and the security challenges needs for implementing them.

Software-Defined Networks (SDN) work by virtualization of the network and the Cognitive Software-Defined Network (CSDN) combines the efficiencies of SDN with cognitive learning algorithms and enhanced protocols to automatize SDN. Partial deployment of SDN along with traditional networking devices forms a Hybrid Software-Defined Network (HSDN). Software-Defined Network Frameworks: Security Issues and Use Cases consolidates the research relating to the security in SDN, CSDN, and Hybrid SDNs. The security enhancements derived from the use of various SDN frameworks and the security challenges thus introduced, are also discussed. Overall, this book explains the different architectures of SDNs and the security challenges needed for implementing them.

Features:

  • Illustrates different frameworks of SDN and their security issues in a single volume
  • Discusses design and assessment of efficient SDN northbound/southbound interfaces
  • Describes cognitive computing, affective computing, machine learning, and other novel tools
  • Illustrates coupling of SDN and traditional networking – Hybrid SDN
  • Explores services, technologies, algorithms, and methods for data analysis in CSDN

The book is aimed at researchers and graduate students in software engineering, network security, computer networks, high performance computing, communications engineering, and intelligent systems.

This book consolidates the research relating to the security in SDN, CSDN, and Hybrid SDNs. The security enhancements derived from use of various SDN frameworks and the security challenges thus introduced, are also discussed. Overall, this book explains different architectures of SDNs and the security challenges needs for implementing them.

Software-Defined Networks (SDN) work by virtualization of the network and the Cognitive Software-Defined Network (CSDN) combines the efficiencies of SDN with cognitive learning algorithms and enhanced protocols to automatize SDN. Partial deployment of SDN along with traditional networking devices forms a Hybrid Software-Defined Network (HSDN). Software-Defined Network Frameworks: Security Issues and Use Cases consolidates the research relating to the security in SDN, CSDN, and Hybrid SDNs. The security enhancements derived from the use of various SDN frameworks and the security challenges thus introduced, are also discussed. Overall, this book explains the different architectures of SDNs and the security challenges needed for implementing them.

Features:

  • Illustrates different frameworks of SDN and their security issues in a single volume
  • Discusses design and assessment of efficient SDN northbound/southbound interfaces
  • Describes cognitive computing, affective computing, machine learning, and other novel tools
  • Illustrates coupling of SDN and traditional networking – Hybrid SDN
  • Explores services, technologies, algorithms, and methods for data analysis in CSDN

The book is aimed at researchers and graduate students in software engineering, network security, computer networks, high performance computing, communications engineering, and intelligent systems.

This book consolidates the research relating to the security in SDN, CSDN, and Hybrid SDNs. The security enhancements derived from use of various SDN frameworks and the security challenges thus introduced, are also discussed. Overall, this book explains different architectures of SDNs and the security challenges needs for implementing them.

Software-Defined Networks (SDN) work by virtualization of the network and the Cognitive Software-Defined Network (CSDN) combines the efficiencies of SDN with cognitive learning algorithms and enhanced protocols to automatize SDN. Partial deployment of SDN along with traditional networking devices forms a Hybrid Software-Defined Network (HSDN). Software-Defined Network Frameworks: Security Issues and Use Cases consolidates the research relating to the security in SDN, CSDN, and Hybrid SDNs. The security enhancements derived from the use of various SDN frameworks and the security challenges thus introduced, are also discussed. Overall, this book explains the different architectures of SDNs and the security challenges needed for implementing them.

Features:

  • Illustrates different frameworks of SDN and their security issues in a single volume
  • Discusses design and assessment of efficient SDN northbound/southbound interfaces
  • Describes cognitive computing, affective computing, machine learning, and other novel tools
  • Illustrates coupling of SDN and traditional networking – Hybrid SDN
  • Explores services, technologies, algorithms, and methods for data analysis in CSDN

The book is aimed at researchers and graduate students in software engineering, network security, computer networks, high performance computing, communications engineering, and intelligent systems.

This book consolidates the research relating to the security in SDN, CSDN, and Hybrid SDNs. The security enhancements derived from use of various SDN frameworks and the security challenges thus introduced, are also discussed. Overall, this book explains different architectures of SDNs and the security challenges needs for implementing them.

Software-Defined Networks (SDN) work by virtualization of the network and the Cognitive Software-Defined Network (CSDN) combines the efficiencies of SDN with cognitive learning algorithms and enhanced protocols to automatize SDN. Partial deployment of SDN along with traditional networking devices forms a Hybrid Software-Defined Network (HSDN). Software-Defined Network Frameworks: Security Issues and Use Cases consolidates the research relating to the security in SDN, CSDN, and Hybrid SDNs. The security enhancements derived from the use of various SDN frameworks and the security challenges thus introduced, are also discussed. Overall, this book explains the different architectures of SDNs and the security challenges needed for implementing them.

Features:

  • Illustrates different frameworks of SDN and their security issues in a single volume
  • Discusses design and assessment of efficient SDN northbound/southbound interfaces
  • Describes cognitive computing, affective computing, machine learning, and other novel tools
  • Illustrates coupling of SDN and traditional networking – Hybrid SDN
  • Explores services, technologies, algorithms, and methods for data analysis in CSDN

The book is aimed at researchers and graduate students in software engineering, network security, computer networks, high performance computing, communications engineering, and intelligent systems.

This book consolidates the research relating to the security in SDN, CSDN, and Hybrid SDNs. The security enhancements derived from use of various SDN frameworks and the security challenges thus introduced, are also discussed. Overall, this book explains different architectures of SDNs and the security challenges needs for implementing them.

Software-Defined Networks (SDN) work by virtualization of the network and the Cognitive Software-Defined Network (CSDN) combines the efficiencies of SDN with cognitive learning algorithms and enhanced protocols to automatize SDN. Partial deployment of SDN along with traditional networking devices forms a Hybrid Software-Defined Network (HSDN). Software-Defined Network Frameworks: Security Issues and Use Cases consolidates the research relating to the security in SDN, CSDN, and Hybrid SDNs. The security enhancements derived from the use of various SDN frameworks and the security challenges thus introduced, are also discussed. Overall, this book explains the different architectures of SDNs and the security challenges needed for implementing them.

Features:

  • Illustrates different frameworks of SDN and their security issues in a single volume
  • Discusses design and assessment of efficient SDN northbound/southbound interfaces
  • Describes cognitive computing, affective computing, machine learning, and other novel tools
  • Illustrates coupling of SDN and traditional networking – Hybrid SDN
  • Explores services, technologies, algorithms, and methods for data analysis in CSDN

The book is aimed at researchers and graduate students in software engineering, network security, computer networks, high performance computing, communications engineering, and intelligent systems.

This book consolidates the research relating to the security in SDN, CSDN, and Hybrid SDNs. The security enhancements derived from use of various SDN frameworks and the security challenges thus introduced, are also discussed. Overall, this book explains different architectures of SDNs and the security challenges needs for implementing them.

Software-Defined Networks (SDN) work by virtualization of the network and the Cognitive Software-Defined Network (CSDN) combines the efficiencies of SDN with cognitive learning algorithms and enhanced protocols to automatize SDN. Partial deployment of SDN along with traditional networking devices forms a Hybrid Software-Defined Network (HSDN). Software-Defined Network Frameworks: Security Issues and Use Cases consolidates the research relating to the security in SDN, CSDN, and Hybrid SDNs. The security enhancements derived from the use of various SDN frameworks and the security challenges thus introduced, are also discussed. Overall, this book explains the different architectures of SDNs and the security challenges needed for implementing them.

Features:

  • Illustrates different frameworks of SDN and their security issues in a single volume
  • Discusses design and assessment of efficient SDN northbound/southbound interfaces
  • Describes cognitive computing, affective computing, machine learning, and other novel tools
  • Illustrates coupling of SDN and traditional networking – Hybrid SDN
  • Explores services, technologies, algorithms, and methods for data analysis in CSDN

The book is aimed at researchers and graduate students in software engineering, network security, computer networks, high performance computing, communications engineering, and intelligent systems.

This book consolidates the research relating to the security in SDN, CSDN, and Hybrid SDNs. The security enhancements derived from use of various SDN frameworks and the security challenges thus introduced, are also discussed. Overall, this book explains different architectures of SDNs and the security challenges needs for implementing them.

Software-Defined Networks (SDN) work by virtualization of the network and the Cognitive Software-Defined Network (CSDN) combines the efficiencies of SDN with cognitive learning algorithms and enhanced protocols to automatize SDN. Partial deployment of SDN along with traditional networking devices forms a Hybrid Software-Defined Network (HSDN). Software-Defined Network Frameworks: Security Issues and Use Cases consolidates the research relating to the security in SDN, CSDN, and Hybrid SDNs. The security enhancements derived from the use of various SDN frameworks and the security challenges thus introduced, are also discussed. Overall, this book explains the different architectures of SDNs and the security challenges needed for implementing them.

Features:

  • Illustrates different frameworks of SDN and their security issues in a single volume
  • Discusses design and assessment of efficient SDN northbound/southbound interfaces
  • Describes cognitive computing, affective computing, machine learning, and other novel tools
  • Illustrates coupling of SDN and traditional networking – Hybrid SDN
  • Explores services, technologies, algorithms, and methods for data analysis in CSDN

The book is aimed at researchers and graduate students in software engineering, network security, computer networks, high performance computing, communications engineering, and intelligent systems.

This book consolidates the research relating to the security in SDN, CSDN, and Hybrid SDNs. The security enhancements derived from use of various SDN frameworks and the security challenges thus introduced, are also discussed. Overall, this book explains different architectures of SDNs and the security challenges needs for implementing them.

Software-Defined Networks (SDN) work by virtualization of the network and the Cognitive Software-Defined Network (CSDN) combines the efficiencies of SDN with cognitive learning algorithms and enhanced protocols to automatize SDN. Partial deployment of SDN along with traditional networking devices forms a Hybrid Software-Defined Network (HSDN). Software-Defined Network Frameworks: Security Issues and Use Cases consolidates the research relating to the security in SDN, CSDN, and Hybrid SDNs. The security enhancements derived from the use of various SDN frameworks and the security challenges thus introduced, are also discussed. Overall, this book explains the different architectures of SDNs and the security challenges needed for implementing them.

Features:

  • Illustrates different frameworks of SDN and their security issues in a single volume
  • Discusses design and assessment of efficient SDN northbound/southbound interfaces
  • Describes cognitive computing, affective computing, machine learning, and other novel tools
  • Illustrates coupling of SDN and traditional networking – Hybrid SDN
  • Explores services, technologies, algorithms, and methods for data analysis in CSDN

The book is aimed at researchers and graduate students in software engineering, network security, computer networks, high performance computing, communications engineering, and intelligent systems.

This book consolidates the research relating to the security in SDN, CSDN, and Hybrid SDNs. The security enhancements derived from use of various SDN frameworks and the security challenges thus introduced, are also discussed. Overall, this book explains different architectures of SDNs and the security challenges needs for implementing them.

Software-Defined Networks (SDN) work by virtualization of the network and the Cognitive Software-Defined Network (CSDN) combines the efficiencies of SDN with cognitive learning algorithms and enhanced protocols to automatize SDN. Partial deployment of SDN along with traditional networking devices forms a Hybrid Software-Defined Network (HSDN). Software-Defined Network Frameworks: Security Issues and Use Cases consolidates the research relating to the security in SDN, CSDN, and Hybrid SDNs. The security enhancements derived from the use of various SDN frameworks and the security challenges thus introduced, are also discussed. Overall, this book explains the different architectures of SDNs and the security challenges needed for implementing them.

Features:

  • Illustrates different frameworks of SDN and their security issues in a single volume
  • Discusses design and assessment of efficient SDN northbound/southbound interfaces
  • Describes cognitive computing, affective computing, machine learning, and other novel tools
  • Illustrates coupling of SDN and traditional networking – Hybrid SDN
  • Explores services, technologies, algorithms, and methods for data analysis in CSDN

The book is aimed at researchers and graduate students in software engineering, network security, computer networks, high performance computing, communications engineering, and intelligent systems.

This book consolidates the research relating to the security in SDN, CSDN, and Hybrid SDNs. The security enhancements derived from use of various SDN frameworks and the security challenges thus introduced, are also discussed. Overall, this book explains different architectures of SDNs and the security challenges needs for implementing them.

Software-Defined Networks (SDN) work by virtualization of the network and the Cognitive Software-Defined Network (CSDN) combines the efficiencies of SDN with cognitive learning algorithms and enhanced protocols to automatize SDN. Partial deployment of SDN along with traditional networking devices forms a Hybrid Software-Defined Network (HSDN). Software-Defined Network Frameworks: Security Issues and Use Cases consolidates the research relating to the security in SDN, CSDN, and Hybrid SDNs. The security enhancements derived from the use of various SDN frameworks and the security challenges thus introduced, are also discussed. Overall, this book explains the different architectures of SDNs and the security challenges needed for implementing them.

Features:

  • Illustrates different frameworks of SDN and their security issues in a single volume
  • Discusses design and assessment of efficient SDN northbound/southbound interfaces
  • Describes cognitive computing, affective computing, machine learning, and other novel tools
  • Illustrates coupling of SDN and traditional networking – Hybrid SDN
  • Explores services, technologies, algorithms, and methods for data analysis in CSDN

The book is aimed at researchers and graduate students in software engineering, network security, computer networks, high performance computing, communications engineering, and intelligent systems.

This book consolidates the research relating to the security in SDN, CSDN, and Hybrid SDNs. The security enhancements derived from use of various SDN frameworks and the security challenges thus introduced, are also discussed. Overall, this book explains different architectures of SDNs and the security challenges needs for implementing them.

Software-Defined Networks (SDN) work by virtualization of the network and the Cognitive Software-Defined Network (CSDN) combines the efficiencies of SDN with cognitive learning algorithms and enhanced protocols to automatize SDN. Partial deployment of SDN along with traditional networking devices forms a Hybrid Software-Defined Network (HSDN). Software-Defined Network Frameworks: Security Issues and Use Cases consolidates the research relating to the security in SDN, CSDN, and Hybrid SDNs. The security enhancements derived from the use of various SDN frameworks and the security challenges thus introduced, are also discussed. Overall, this book explains the different architectures of SDNs and the security challenges needed for implementing them.

Features:

  • Illustrates different frameworks of SDN and their security issues in a single volume
  • Discusses design and assessment of efficient SDN northbound/southbound interfaces
  • Describes cognitive computing, affective computing, machine learning, and other novel tools
  • Illustrates coupling of SDN and traditional networking – Hybrid SDN
  • Explores services, technologies, algorithms, and methods for data analysis in CSDN

The book is aimed at researchers and graduate students in software engineering, network security, computer networks, high performance computing, communications engineering, and intelligent systems.

This book consolidates the research relating to the security in SDN, CSDN, and Hybrid SDNs. The security enhancements derived from use of various SDN frameworks and the security challenges thus introduced, are also discussed. Overall, this book explains different architectures of SDNs and the security challenges needs for implementing them.

Software-Defined Networks (SDN) work by virtualization of the network and the Cognitive Software-Defined Network (CSDN) combines the efficiencies of SDN with cognitive learning algorithms and enhanced protocols to automatize SDN. Partial deployment of SDN along with traditional networking devices forms a Hybrid Software-Defined Network (HSDN). Software-Defined Network Frameworks: Security Issues and Use Cases consolidates the research relating to the security in SDN, CSDN, and Hybrid SDNs. The security enhancements derived from the use of various SDN frameworks and the security challenges thus introduced, are also discussed. Overall, this book explains the different architectures of SDNs and the security challenges needed for implementing them.

Features:

  • Illustrates different frameworks of SDN and their security issues in a single volume
  • Discusses design and assessment of efficient SDN northbound/southbound interfaces
  • Describes cognitive computing, affective computing, machine learning, and other novel tools
  • Illustrates coupling of SDN and traditional networking – Hybrid SDN
  • Explores services, technologies, algorithms, and methods for data analysis in CSDN

The book is aimed at researchers and graduate students in software engineering, network security, computer networks, high performance computing, communications engineering, and intelligent systems.

This book consolidates the research relating to the security in SDN, CSDN, and Hybrid SDNs. The security enhancements derived from use of various SDN frameworks and the security challenges thus introduced, are also discussed. Overall, this book explains different architectures of SDNs and the security challenges needs for implementing them.

Software-Defined Networks (SDN) work by virtualization of the network and the Cognitive Software-Defined Network (CSDN) combines the efficiencies of SDN with cognitive learning algorithms and enhanced protocols to automatize SDN. Partial deployment of SDN along with traditional networking devices forms a Hybrid Software-Defined Network (HSDN). Software-Defined Network Frameworks: Security Issues and Use Cases consolidates the research relating to the security in SDN, CSDN, and Hybrid SDNs. The security enhancements derived from the use of various SDN frameworks and the security challenges thus introduced, are also discussed. Overall, this book explains the different architectures of SDNs and the security challenges needed for implementing them.

Features:

  • Illustrates different frameworks of SDN and their security issues in a single volume
  • Discusses design and assessment of efficient SDN northbound/southbound interfaces
  • Describes cognitive computing, affective computing, machine learning, and other novel tools
  • Illustrates coupling of SDN and traditional networking – Hybrid SDN
  • Explores services, technologies, algorithms, and methods for data analysis in CSDN

The book is aimed at researchers and graduate students in software engineering, network security, computer networks, high performance computing, communications engineering, and intelligent systems.

This book consolidates the research relating to the security in SDN, CSDN, and Hybrid SDNs. The security enhancements derived from use of various SDN frameworks and the security challenges thus introduced, are also discussed. Overall, this book explains different architectures of SDNs and the security challenges needs for implementing them.

Software-Defined Networks (SDN) work by virtualization of the network and the Cognitive Software-Defined Network (CSDN) combines the efficiencies of SDN with cognitive learning algorithms and enhanced protocols to automatize SDN. Partial deployment of SDN along with traditional networking devices forms a Hybrid Software-Defined Network (HSDN). Software-Defined Network Frameworks: Security Issues and Use Cases consolidates the research relating to the security in SDN, CSDN, and Hybrid SDNs. The security enhancements derived from the use of various SDN frameworks and the security challenges thus introduced, are also discussed. Overall, this book explains the different architectures of SDNs and the security challenges needed for implementing them.

Features:

  • Illustrates different frameworks of SDN and their security issues in a single volume
  • Discusses design and assessment of efficient SDN northbound/southbound interfaces
  • Describes cognitive computing, affective computing, machine learning, and other novel tools
  • Illustrates coupling of SDN and traditional networking – Hybrid SDN
  • Explores services, technologies, algorithms, and methods for data analysis in CSDN

The book is aimed at researchers and graduate students in software engineering, network security, computer networks, high performance computing, communications engineering, and intelligent systems.

This book consolidates the research relating to the security in SDN, CSDN, and Hybrid SDNs. The security enhancements derived from use of various SDN frameworks and the security challenges thus introduced, are also discussed. Overall, this book explains different architectures of SDNs and the security challenges needs for implementing them.

Software-Defined Networks (SDN) work by virtualization of the network and the Cognitive Software-Defined Network (CSDN) combines the efficiencies of SDN with cognitive learning algorithms and enhanced protocols to automatize SDN. Partial deployment of SDN along with traditional networking devices forms a Hybrid Software-Defined Network (HSDN). Software-Defined Network Frameworks: Security Issues and Use Cases consolidates the research relating to the security in SDN, CSDN, and Hybrid SDNs. The security enhancements derived from the use of various SDN frameworks and the security challenges thus introduced, are also discussed. Overall, this book explains the different architectures of SDNs and the security challenges needed for implementing them.

Features:

  • Illustrates different frameworks of SDN and their security issues in a single volume
  • Discusses design and assessment of efficient SDN northbound/southbound interfaces
  • Describes cognitive computing, affective computing, machine learning, and other novel tools
  • Illustrates coupling of SDN and traditional networking – Hybrid SDN
  • Explores services, technologies, algorithms, and methods for data analysis in CSDN

The book is aimed at researchers and graduate students in software engineering, network security, computer networks, high performance computing, communications engineering, and intelligent systems.

This book consolidates the research relating to the security in SDN, CSDN, and Hybrid SDNs. The security enhancements derived from use of various SDN frameworks and the security challenges thus introduced, are also discussed. Overall, this book explains different architectures of SDNs and the security challenges needs for implementing them.

Software-Defined Networks (SDN) work by virtualization of the network and the Cognitive Software-Defined Network (CSDN) combines the efficiencies of SDN with cognitive learning algorithms and enhanced protocols to automatize SDN. Partial deployment of SDN along with traditional networking devices forms a Hybrid Software-Defined Network (HSDN). Software-Defined Network Frameworks: Security Issues and Use Cases consolidates the research relating to the security in SDN, CSDN, and Hybrid SDNs. The security enhancements derived from the use of various SDN frameworks and the security challenges thus introduced, are also discussed. Overall, this book explains the different architectures of SDNs and the security challenges needed for implementing them.

Features:

  • Illustrates different frameworks of SDN and their security issues in a single volume
  • Discusses design and assessment of efficient SDN northbound/southbound interfaces
  • Describes cognitive computing, affective computing, machine learning, and other novel tools
  • Illustrates coupling of SDN and traditional networking – Hybrid SDN
  • Explores services, technologies, algorithms, and methods for data analysis in CSDN

The book is aimed at researchers and graduate students in software engineering, network security, computer networks, high performance computing, communications engineering, and intelligent systems.

This book consolidates the research relating to the security in SDN, CSDN, and Hybrid SDNs. The security enhancements derived from use of various SDN frameworks and the security challenges thus introduced, are also discussed. Overall, this book explains different architectures of SDNs and the security challenges needs for implementing them.

Software-Defined Networks (SDN) work by virtualization of the network and the Cognitive Software-Defined Network (CSDN) combines the efficiencies of SDN with cognitive learning algorithms and enhanced protocols to automatize SDN. Partial deployment of SDN along with traditional networking devices forms a Hybrid Software-Defined Network (HSDN). Software-Defined Network Frameworks: Security Issues and Use Cases consolidates the research relating to the security in SDN, CSDN, and Hybrid SDNs. The security enhancements derived from the use of various SDN frameworks and the security challenges thus introduced, are also discussed. Overall, this book explains the different architectures of SDNs and the security challenges needed for implementing them.

Features:

  • Illustrates different frameworks of SDN and their security issues in a single volume
  • Discusses design and assessment of efficient SDN northbound/southbound interfaces
  • Describes cognitive computing, affective computing, machine learning, and other novel tools
  • Illustrates coupling of SDN and traditional networking – Hybrid SDN
  • Explores services, technologies, algorithms, and methods for data analysis in CSDN

The book is aimed at researchers and graduate students in software engineering, network security, computer networks, high performance computing, communications engineering, and intelligent systems.

This book consolidates the research relating to the security in SDN, CSDN, and Hybrid SDNs. The security enhancements derived from use of various SDN frameworks and the security challenges thus introduced, are also discussed. Overall, this book explains different architectures of SDNs and the security challenges needs for implementing them.

Software-Defined Networks (SDN) work by virtualization of the network and the Cognitive Software-Defined Network (CSDN) combines the efficiencies of SDN with cognitive learning algorithms and enhanced protocols to automatize SDN. Partial deployment of SDN along with traditional networking devices forms a Hybrid Software-Defined Network (HSDN). Software-Defined Network Frameworks: Security Issues and Use Cases consolidates the research relating to the security in SDN, CSDN, and Hybrid SDNs. The security enhancements derived from the use of various SDN frameworks and the security challenges thus introduced, are also discussed. Overall, this book explains the different architectures of SDNs and the security challenges needed for implementing them.

Features:

  • Illustrates different frameworks of SDN and their security issues in a single volume
  • Discusses design and assessment of efficient SDN northbound/southbound interfaces
  • Describes cognitive computing, affective computing, machine learning, and other novel tools
  • Illustrates coupling of SDN and traditional networking – Hybrid SDN
  • Explores services, technologies, algorithms, and methods for data analysis in CSDN

The book is aimed at researchers and graduate students in software engineering, network security, computer networks, high performance computing, communications engineering, and intelligent systems.

This book consolidates the research relating to the security in SDN, CSDN, and Hybrid SDNs. The security enhancements derived from use of various SDN frameworks and the security challenges thus introduced, are also discussed. Overall, this book explains different architectures of SDNs and the security challenges needs for implementing them.

Software-Defined Networks (SDN) work by virtualization of the network and the Cognitive Software-Defined Network (CSDN) combines the efficiencies of SDN with cognitive learning algorithms and enhanced protocols to automatize SDN. Partial deployment of SDN along with traditional networking devices forms a Hybrid Software-Defined Network (HSDN). Software-Defined Network Frameworks: Security Issues and Use Cases consolidates the research relating to the security in SDN, CSDN, and Hybrid SDNs. The security enhancements derived from the use of various SDN frameworks and the security challenges thus introduced, are also discussed. Overall, this book explains the different architectures of SDNs and the security challenges needed for implementing them.

Features:

  • Illustrates different frameworks of SDN and their security issues in a single volume
  • Discusses design and assessment of efficient SDN northbound/southbound interfaces
  • Describes cognitive computing, affective computing, machine learning, and other novel tools
  • Illustrates coupling of SDN and traditional networking – Hybrid SDN
  • Explores services, technologies, algorithms, and methods for data analysis in CSDN

The book is aimed at researchers and graduate students in software engineering, network security, computer networks, high performance computing, communications engineering, and intelligent systems.

This book consolidates the research relating to the security in SDN, CSDN, and Hybrid SDNs. The security enhancements derived from use of various SDN frameworks and the security challenges thus introduced, are also discussed. Overall, this book explains different architectures of SDNs and the security challenges needs for implementing them.

Software-Defined Networks (SDN) work by virtualization of the network and the Cognitive Software-Defined Network (CSDN) combines the efficiencies of SDN with cognitive learning algorithms and enhanced protocols to automatize SDN. Partial deployment of SDN along with traditional networking devices forms a Hybrid Software-Defined Network (HSDN). Software-Defined Network Frameworks: Security Issues and Use Cases consolidates the research relating to the security in SDN, CSDN, and Hybrid SDNs. The security enhancements derived from the use of various SDN frameworks and the security challenges thus introduced, are also discussed. Overall, this book explains the different architectures of SDNs and the security challenges needed for implementing them.

Features:

  • Illustrates different frameworks of SDN and their security issues in a single volume
  • Discusses design and assessment of efficient SDN northbound/southbound interfaces
  • Describes cognitive computing, affective computing, machine learning, and other novel tools
  • Illustrates coupling of SDN and traditional networking – Hybrid SDN
  • Explores services, technologies, algorithms, and methods for data analysis in CSDN

The book is aimed at researchers and graduate students in software engineering, network security, computer networks, high performance computing, communications engineering, and intelligent systems.

This book consolidates the research relating to the security in SDN, CSDN, and Hybrid SDNs. The security enhancements derived from use of various SDN frameworks and the security challenges thus introduced, are also discussed. Overall, this book explains different architectures of SDNs and the security challenges needs for implementing them.

Software-Defined Networks (SDN) work by virtualization of the network and the Cognitive Software-Defined Network (CSDN) combines the efficiencies of SDN with cognitive learning algorithms and enhanced protocols to automatize SDN. Partial deployment of SDN along with traditional networking devices forms a Hybrid Software-Defined Network (HSDN). Software-Defined Network Frameworks: Security Issues and Use Cases consolidates the research relating to the security in SDN, CSDN, and Hybrid SDNs. The security enhancements derived from the use of various SDN frameworks and the security challenges thus introduced, are also discussed. Overall, this book explains the different architectures of SDNs and the security challenges needed for implementing them.

Features:

  • Illustrates different frameworks of SDN and their security issues in a single volume
  • Discusses design and assessment of efficient SDN northbound/southbound interfaces
  • Describes cognitive computing, affective computing, machine learning, and other novel tools
  • Illustrates coupling of SDN and traditional networking – Hybrid SDN
  • Explores services, technologies, algorithms, and methods for data analysis in CSDN

The book is aimed at researchers and graduate students in software engineering, network security, computer networks, high performance computing, communications engineering, and intelligent systems.

This book consolidates the research relating to the security in SDN, CSDN, and Hybrid SDNs. The security enhancements derived from use of various SDN frameworks and the security challenges thus introduced, are also discussed. Overall, this book explains different architectures of SDNs and the security challenges needs for implementing them.

Software-Defined Networks (SDN) work by virtualization of the network and the Cognitive Software-Defined Network (CSDN) combines the efficiencies of SDN with cognitive learning algorithms and enhanced protocols to automatize SDN. Partial deployment of SDN along with traditional networking devices forms a Hybrid Software-Defined Network (HSDN). Software-Defined Network Frameworks: Security Issues and Use Cases consolidates the research relating to the security in SDN, CSDN, and Hybrid SDNs. The security enhancements derived from the use of various SDN frameworks and the security challenges thus introduced, are also discussed. Overall, this book explains the different architectures of SDNs and the security challenges needed for implementing them.

Features:

  • Illustrates different frameworks of SDN and their security issues in a single volume
  • Discusses design and assessment of efficient SDN northbound/southbound interfaces
  • Describes cognitive computing, affective computing, machine learning, and other novel tools
  • Illustrates coupling of SDN and traditional networking – Hybrid SDN
  • Explores services, technologies, algorithms, and methods for data analysis in CSDN

The book is aimed at researchers and graduate students in software engineering, network security, computer networks, high performance computing, communications engineering, and intelligent systems.

This book consolidates the research relating to the security in SDN, CSDN, and Hybrid SDNs. The security enhancements derived from use of various SDN frameworks and the security challenges thus introduced, are also discussed. Overall, this book explains different architectures of SDNs and the security challenges needs for implementing them.

Software-Defined Networks (SDN) work by virtualization of the network and the Cognitive Software-Defined Network (CSDN) combines the efficiencies of SDN with cognitive learning algorithms and enhanced protocols to automatize SDN. Partial deployment of SDN along with traditional networking devices forms a Hybrid Software-Defined Network (HSDN). Software-Defined Network Frameworks: Security Issues and Use Cases consolidates the research relating to the security in SDN, CSDN, and Hybrid SDNs. The security enhancements derived from the use of various SDN frameworks and the security challenges thus introduced, are also discussed. Overall, this book explains the different architectures of SDNs and the security challenges needed for implementing them.

Features:

  • Illustrates different frameworks of SDN and their security issues in a single volume
  • Discusses design and assessment of efficient SDN northbound/southbound interfaces
  • Describes cognitive computing, affective computing, machine learning, and other novel tools
  • Illustrates coupling of SDN and traditional networking – Hybrid SDN
  • Explores services, technologies, algorithms, and methods for data analysis in CSDN

The book is aimed at researchers and graduate students in software engineering, network security, computer networks, high performance computing, communications engineering, and intelligent systems.

This book consolidates the research relating to the security in SDN, CSDN, and Hybrid SDNs. The security enhancements derived from use of various SDN frameworks and the security challenges thus introduced, are also discussed. Overall, this book explains different architectures of SDNs and the security challenges needs for implementing them.

Software-Defined Networks (SDN) work by virtualization of the network and the Cognitive Software-Defined Network (CSDN) combines the efficiencies of SDN with cognitive learning algorithms and enhanced protocols to automatize SDN. Partial deployment of SDN along with traditional networking devices forms a Hybrid Software-Defined Network (HSDN). Software-Defined Network Frameworks: Security Issues and Use Cases consolidates the research relating to the security in SDN, CSDN, and Hybrid SDNs. The security enhancements derived from the use of various SDN frameworks and the security challenges thus introduced, are also discussed. Overall, this book explains the different architectures of SDNs and the security challenges needed for implementing them.

Features:

  • Illustrates different frameworks of SDN and their security issues in a single volume
  • Discusses design and assessment of efficient SDN northbound/southbound interfaces
  • Describes cognitive computing, affective computing, machine learning, and other novel tools
  • Illustrates coupling of SDN and traditional networking – Hybrid SDN
  • Explores services, technologies, algorithms, and methods for data analysis in CSDN

The book is aimed at researchers and graduate students in software engineering, network security, computer networks, high performance computing, communications engineering, and intelligent systems.

This book consolidates the research relating to the security in SDN, CSDN, and Hybrid SDNs. The security enhancements derived from use of various SDN frameworks and the security challenges thus introduced, are also discussed. Overall, this book explains different architectures of SDNs and the security challenges needs for implementing them.

Software-Defined Networks (SDN) work by virtualization of the network and the Cognitive Software-Defined Network (CSDN) combines the efficiencies of SDN with cognitive learning algorithms and enhanced protocols to automatize SDN. Partial deployment of SDN along with traditional networking devices forms a Hybrid Software-Defined Network (HSDN). Software-Defined Network Frameworks: Security Issues and Use Cases consolidates the research relating to the security in SDN, CSDN, and Hybrid SDNs. The security enhancements derived from the use of various SDN frameworks and the security challenges thus introduced, are also discussed. Overall, this book explains the different architectures of SDNs and the security challenges needed for implementing them.

Features:

  • Illustrates different frameworks of SDN and their security issues in a single volume
  • Discusses design and assessment of efficient SDN northbound/southbound interfaces
  • Describes cognitive computing, affective computing, machine learning, and other novel tools
  • Illustrates coupling of SDN and traditional networking – Hybrid SDN
  • Explores services, technologies, algorithms, and methods for data analysis in CSDN

The book is aimed at researchers and graduate students in software engineering, network security, computer networks, high performance computing, communications engineering, and intelligent systems.

This book consolidates the research relating to the security in SDN, CSDN, and Hybrid SDNs. The security enhancements derived from use of various SDN frameworks and the security challenges thus introduced, are also discussed. Overall, this book explains different architectures of SDNs and the security challenges needs for implementing them.

Software-Defined Networks (SDN) work by virtualization of the network and the Cognitive Software-Defined Network (CSDN) combines the efficiencies of SDN with cognitive learning algorithms and enhanced protocols to automatize SDN. Partial deployment of SDN along with traditional networking devices forms a Hybrid Software-Defined Network (HSDN). Software-Defined Network Frameworks: Security Issues and Use Cases consolidates the research relating to the security in SDN, CSDN, and Hybrid SDNs. The security enhancements derived from the use of various SDN frameworks and the security challenges thus introduced, are also discussed. Overall, this book explains the different architectures of SDNs and the security challenges needed for implementing them.

Features:

  • Illustrates different frameworks of SDN and their security issues in a single volume
  • Discusses design and assessment of efficient SDN northbound/southbound interfaces
  • Describes cognitive computing, affective computing, machine learning, and other novel tools
  • Illustrates coupling of SDN and traditional networking – Hybrid SDN
  • Explores services, technologies, algorithms, and methods for data analysis in CSDN

The book is aimed at researchers and graduate students in software engineering, network security, computer networks, high performance computing, communications engineering, and intelligent systems.

This book consolidates the research relating to the security in SDN, CSDN, and Hybrid SDNs. The security enhancements derived from use of various SDN frameworks and the security challenges thus introduced, are also discussed. Overall, this book explains different architectures of SDNs and the security challenges needs for implementing them.

Software-Defined Networks (SDN) work by virtualization of the network and the Cognitive Software-Defined Network (CSDN) combines the efficiencies of SDN with cognitive learning algorithms and enhanced protocols to automatize SDN. Partial deployment of SDN along with traditional networking devices forms a Hybrid Software-Defined Network (HSDN). Software-Defined Network Frameworks: Security Issues and Use Cases consolidates the research relating to the security in SDN, CSDN, and Hybrid SDNs. The security enhancements derived from the use of various SDN frameworks and the security challenges thus introduced, are also discussed. Overall, this book explains the different architectures of SDNs and the security challenges needed for implementing them.

Features:

  • Illustrates different frameworks of SDN and their security issues in a single volume
  • Discusses design and assessment of efficient SDN northbound/southbound interfaces
  • Describes cognitive computing, affective computing, machine learning, and other novel tools
  • Illustrates coupling of SDN and traditional networking – Hybrid SDN
  • Explores services, technologies, algorithms, and methods for data analysis in CSDN

The book is aimed at researchers and graduate students in software engineering, network security, computer networks, high performance computing, communications engineering, and intelligent systems.

This book consolidates the research relating to the security in SDN, CSDN, and Hybrid SDNs. The security enhancements derived from use of various SDN frameworks and the security challenges thus introduced, are also discussed. Overall, this book explains different architectures of SDNs and the security challenges needs for implementing them.

Software-Defined Networks (SDN) work by virtualization of the network and the Cognitive Software-Defined Network (CSDN) combines the efficiencies of SDN with cognitive learning algorithms and enhanced protocols to automatize SDN. Partial deployment of SDN along with traditional networking devices forms a Hybrid Software-Defined Network (HSDN). Software-Defined Network Frameworks: Security Issues and Use Cases consolidates the research relating to the security in SDN, CSDN, and Hybrid SDNs. The security enhancements derived from the use of various SDN frameworks and the security challenges thus introduced, are also discussed. Overall, this book explains the different architectures of SDNs and the security challenges needed for implementing them.

Features:

  • Illustrates different frameworks of SDN and their security issues in a single volume
  • Discusses design and assessment of efficient SDN northbound/southbound interfaces
  • Describes cognitive computing, affective computing, machine learning, and other novel tools
  • Illustrates coupling of SDN and traditional networking – Hybrid SDN
  • Explores services, technologies, algorithms, and methods for data analysis in CSDN

The book is aimed at researchers and graduate students in software engineering, network security, computer networks, high performance computing, communications engineering, and intelligent systems.

This book consolidates the research relating to the security in SDN, CSDN, and Hybrid SDNs. The security enhancements derived from use of various SDN frameworks and the security challenges thus introduced, are also discussed. Overall, this book explains different architectures of SDNs and the security challenges needs for implementing them.

Software-Defined Networks (SDN) work by virtualization of the network and the Cognitive Software-Defined Network (CSDN) combines the efficiencies of SDN with cognitive learning algorithms and enhanced protocols to automatize SDN. Partial deployment of SDN along with traditional networking devices forms a Hybrid Software-Defined Network (HSDN). Software-Defined Network Frameworks: Security Issues and Use Cases consolidates the research relating to the security in SDN, CSDN, and Hybrid SDNs. The security enhancements derived from the use of various SDN frameworks and the security challenges thus introduced, are also discussed. Overall, this book explains the different architectures of SDNs and the security challenges needed for implementing them.

Features:

  • Illustrates different frameworks of SDN and their security issues in a single volume
  • Discusses design and assessment of efficient SDN northbound/southbound interfaces
  • Describes cognitive computing, affective computing, machine learning, and other novel tools
  • Illustrates coupling of SDN and traditional networking – Hybrid SDN
  • Explores services, technologies, algorithms, and methods for data analysis in CSDN

The book is aimed at researchers and graduate students in software engineering, network security, computer networks, high performance computing, communications engineering, and intelligent systems.

This book consolidates the research relating to the security in SDN, CSDN, and Hybrid SDNs. The security enhancements derived from use of various SDN frameworks and the security challenges thus introduced, are also discussed. Overall, this book explains different architectures of SDNs and the security challenges needs for implementing them.

Software-Defined Networks (SDN) work by virtualization of the network and the Cognitive Software-Defined Network (CSDN) combines the efficiencies of SDN with cognitive learning algorithms and enhanced protocols to automatize SDN. Partial deployment of SDN along with traditional networking devices forms a Hybrid Software-Defined Network (HSDN). Software-Defined Network Frameworks: Security Issues and Use Cases consolidates the research relating to the security in SDN, CSDN, and Hybrid SDNs. The security enhancements derived from the use of various SDN frameworks and the security challenges thus introduced, are also discussed. Overall, this book explains the different architectures of SDNs and the security challenges needed for implementing them.

Features:

  • Illustrates different frameworks of SDN and their security issues in a single volume
  • Discusses design and assessment of efficient SDN northbound/southbound interfaces
  • Describes cognitive computing, affective computing, machine learning, and other novel tools
  • Illustrates coupling of SDN and traditional networking – Hybrid SDN
  • Explores services, technologies, algorithms, and methods for data analysis in CSDN

The book is aimed at researchers and graduate students in software engineering, network security, computer networks, high performance computing, communications engineering, and intelligent systems.

This book consolidates the research relating to the security in SDN, CSDN, and Hybrid SDNs. The security enhancements derived from use of various SDN frameworks and the security challenges thus introduced, are also discussed. Overall, this book explains different architectures of SDNs and the security challenges needs for implementing them.

Software-Defined Networks (SDN) work by virtualization of the network and the Cognitive Software-Defined Network (CSDN) combines the efficiencies of SDN with cognitive learning algorithms and enhanced protocols to automatize SDN. Partial deployment of SDN along with traditional networking devices forms a Hybrid Software-Defined Network (HSDN). Software-Defined Network Frameworks: Security Issues and Use Cases consolidates the research relating to the security in SDN, CSDN, and Hybrid SDNs. The security enhancements derived from the use of various SDN frameworks and the security challenges thus introduced, are also discussed. Overall, this book explains the different architectures of SDNs and the security challenges needed for implementing them.

Features:

  • Illustrates different frameworks of SDN and their security issues in a single volume
  • Discusses design and assessment of efficient SDN northbound/southbound interfaces
  • Describes cognitive computing, affective computing, machine learning, and other novel tools
  • Illustrates coupling of SDN and traditional networking – Hybrid SDN
  • Explores services, technologies, algorithms, and methods for data analysis in CSDN

The book is aimed at researchers and graduate students in software engineering, network security, computer networks, high performance computing, communications engineering, and intelligent systems.

This book consolidates the research relating to the security in SDN, CSDN, and Hybrid SDNs. The security enhancements derived from use of various SDN frameworks and the security challenges thus introduced, are also discussed. Overall, this book explains different architectures of SDNs and the security challenges needs for implementing them.

Software-Defined Networks (SDN) work by virtualization of the network and the Cognitive Software-Defined Network (CSDN) combines the efficiencies of SDN with cognitive learning algorithms and enhanced protocols to automatize SDN. Partial deployment of SDN along with traditional networking devices forms a Hybrid Software-Defined Network (HSDN). Software-Defined Network Frameworks: Security Issues and Use Cases consolidates the research relating to the security in SDN, CSDN, and Hybrid SDNs. The security enhancements derived from the use of various SDN frameworks and the security challenges thus introduced, are also discussed. Overall, this book explains the different architectures of SDNs and the security challenges needed for implementing them.

Features:

  • Illustrates different frameworks of SDN and their security issues in a single volume
  • Discusses design and assessment of efficient SDN northbound/southbound interfaces
  • Describes cognitive computing, affective computing, machine learning, and other novel tools
  • Illustrates coupling of SDN and traditional networking – Hybrid SDN
  • Explores services, technologies, algorithms, and methods for data analysis in CSDN

The book is aimed at researchers and graduate students in software engineering, network security, computer networks, high performance computing, communications engineering, and intelligent systems.

This book consolidates the research relating to the security in SDN, CSDN, and Hybrid SDNs. The security enhancements derived from use of various SDN frameworks and the security challenges thus introduced, are also discussed. Overall, this book explains different architectures of SDNs and the security challenges needs for implementing them.

Software-Defined Networks (SDN) work by virtualization of the network and the Cognitive Software-Defined Network (CSDN) combines the efficiencies of SDN with cognitive learning algorithms and enhanced protocols to automatize SDN. Partial deployment of SDN along with traditional networking devices forms a Hybrid Software-Defined Network (HSDN). Software-Defined Network Frameworks: Security Issues and Use Cases consolidates the research relating to the security in SDN, CSDN, and Hybrid SDNs. The security enhancements derived from the use of various SDN frameworks and the security challenges thus introduced, are also discussed. Overall, this book explains the different architectures of SDNs and the security challenges needed for implementing them.

Features:

  • Illustrates different frameworks of SDN and their security issues in a single volume
  • Discusses design and assessment of efficient SDN northbound/southbound interfaces
  • Describes cognitive computing, affective computing, machine learning, and other novel tools
  • Illustrates coupling of SDN and traditional networking – Hybrid SDN
  • Explores services, technologies, algorithms, and methods for data analysis in CSDN

The book is aimed at researchers and graduate students in software engineering, network security, computer networks, high performance computing, communications engineering, and intelligent systems.

This book consolidates the research relating to the security in SDN, CSDN, and Hybrid SDNs. The security enhancements derived from use of various SDN frameworks and the security challenges thus introduced, are also discussed. Overall, this book explains different architectures of SDNs and the security challenges needs for implementing them.

Software-Defined Networks (SDN) work by virtualization of the network and the Cognitive Software-Defined Network (CSDN) combines the efficiencies of SDN with cognitive learning algorithms and enhanced protocols to automatize SDN. Partial deployment of SDN along with traditional networking devices forms a Hybrid Software-Defined Network (HSDN). Software-Defined Network Frameworks: Security Issues and Use Cases consolidates the research relating to the security in SDN, CSDN, and Hybrid SDNs. The security enhancements derived from the use of various SDN frameworks and the security challenges thus introduced, are also discussed. Overall, this book explains the different architectures of SDNs and the security challenges needed for implementing them.

Features:

  • Illustrates different frameworks of SDN and their security issues in a single volume
  • Discusses design and assessment of efficient SDN northbound/southbound interfaces
  • Describes cognitive computing, affective computing, machine learning, and other novel tools
  • Illustrates coupling of SDN and traditional networking – Hybrid SDN
  • Explores services, technologies, algorithms, and methods for data analysis in CSDN

The book is aimed at researchers and graduate students in software engineering, network security, computer networks, high performance computing, communications engineering, and intelligent systems.

This book consolidates the research relating to the security in SDN, CSDN, and Hybrid SDNs. The security enhancements derived from use of various SDN frameworks and the security challenges thus introduced, are also discussed. Overall, this book explains different architectures of SDNs and the security challenges needs for implementing them.

Software-Defined Networks (SDN) work by virtualization of the network and the Cognitive Software-Defined Network (CSDN) combines the efficiencies of SDN with cognitive learning algorithms and enhanced protocols to automatize SDN. Partial deployment of SDN along with traditional networking devices forms a Hybrid Software-Defined Network (HSDN). Software-Defined Network Frameworks: Security Issues and Use Cases consolidates the research relating to the security in SDN, CSDN, and Hybrid SDNs. The security enhancements derived from the use of various SDN frameworks and the security challenges thus introduced, are also discussed. Overall, this book explains the different architectures of SDNs and the security challenges needed for implementing them.

Features:

  • Illustrates different frameworks of SDN and their security issues in a single volume
  • Discusses design and assessment of efficient SDN northbound/southbound interfaces
  • Describes cognitive computing, affective computing, machine learning, and other novel tools
  • Illustrates coupling of SDN and traditional networking – Hybrid SDN
  • Explores services, technologies, algorithms, and methods for data analysis in CSDN

The book is aimed at researchers and graduate students in software engineering, network security, computer networks, high performance computing, communications engineering, and intelligent systems.

This book consolidates the research relating to the security in SDN, CSDN, and Hybrid SDNs. The security enhancements derived from use of various SDN frameworks and the security challenges thus introduced, are also discussed. Overall, this book explains different architectures of SDNs and the security challenges needs for implementing them.

Software-Defined Networks (SDN) work by virtualization of the network and the Cognitive Software-Defined Network (CSDN) combines the efficiencies of SDN with cognitive learning algorithms and enhanced protocols to automatize SDN. Partial deployment of SDN along with traditional networking devices forms a Hybrid Software-Defined Network (HSDN). Software-Defined Network Frameworks: Security Issues and Use Cases consolidates the research relating to the security in SDN, CSDN, and Hybrid SDNs. The security enhancements derived from the use of various SDN frameworks and the security challenges thus introduced, are also discussed. Overall, this book explains the different architectures of SDNs and the security challenges needed for implementing them.

Features:

  • Illustrates different frameworks of SDN and their security issues in a single volume
  • Discusses design and assessment of efficient SDN northbound/southbound interfaces
  • Describes cognitive computing, affective computing, machine learning, and other novel tools
  • Illustrates coupling of SDN and traditional networking – Hybrid SDN
  • Explores services, technologies, algorithms, and methods for data analysis in CSDN

The book is aimed at researchers and graduate students in software engineering, network security, computer networks, high performance computing, communications engineering, and intelligent systems.

This book consolidates the research relating to the security in SDN, CSDN, and Hybrid SDNs. The security enhancements derived from use of various SDN frameworks and the security challenges thus introduced, are also discussed. Overall, this book explains different architectures of SDNs and the security challenges needs for implementing them.

Software-Defined Networks (SDN) work by virtualization of the network and the Cognitive Software-Defined Network (CSDN) combines the efficiencies of SDN with cognitive learning algorithms and enhanced protocols to automatize SDN. Partial deployment of SDN along with traditional networking devices forms a Hybrid Software-Defined Network (HSDN). Software-Defined Network Frameworks: Security Issues and Use Cases consolidates the research relating to the security in SDN, CSDN, and Hybrid SDNs. The security enhancements derived from the use of various SDN frameworks and the security challenges thus introduced, are also discussed. Overall, this book explains the different architectures of SDNs and the security challenges needed for implementing them.

Features:

  • Illustrates different frameworks of SDN and their security issues in a single volume
  • Discusses design and assessment of efficient SDN northbound/southbound interfaces
  • Describes cognitive computing, affective computing, machine learning, and other novel tools
  • Illustrates coupling of SDN and traditional networking – Hybrid SDN
  • Explores services, technologies, algorithms, and methods for data analysis in CSDN

The book is aimed at researchers and graduate students in software engineering, network security, computer networks, high performance computing, communications engineering, and intelligent systems.

This book consolidates the research relating to the security in SDN, CSDN, and Hybrid SDNs. The security enhancements derived from use of various SDN frameworks and the security challenges thus introduced, are also discussed. Overall, this book explains different architectures of SDNs and the security challenges needs for implementing them.

Software-Defined Networks (SDN) work by virtualization of the network and the Cognitive Software-Defined Network (CSDN) combines the efficiencies of SDN with cognitive learning algorithms and enhanced protocols to automatize SDN. Partial deployment of SDN along with traditional networking devices forms a Hybrid Software-Defined Network (HSDN). Software-Defined Network Frameworks: Security Issues and Use Cases consolidates the research relating to the security in SDN, CSDN, and Hybrid SDNs. The security enhancements derived from the use of various SDN frameworks and the security challenges thus introduced, are also discussed. Overall, this book explains the different architectures of SDNs and the security challenges needed for implementing them.

Features:

  • Illustrates different frameworks of SDN and their security issues in a single volume
  • Discusses design and assessment of efficient SDN northbound/southbound interfaces
  • Describes cognitive computing, affective computing, machine learning, and other novel tools
  • Illustrates coupling of SDN and traditional networking – Hybrid SDN
  • Explores services, technologies, algorithms, and methods for data analysis in CSDN

The book is aimed at researchers and graduate students in software engineering, network security, computer networks, high performance computing, communications engineering, and intelligent systems.

This book consolidates the research relating to the security in SDN, CSDN, and Hybrid SDNs. The security enhancements derived from use of various SDN frameworks and the security challenges thus introduced, are also discussed. Overall, this book explains different architectures of SDNs and the security challenges needs for implementing them.

Software-Defined Networks (SDN) work by virtualization of the network and the Cognitive Software-Defined Network (CSDN) combines the efficiencies of SDN with cognitive learning algorithms and enhanced protocols to automatize SDN. Partial deployment of SDN along with traditional networking devices forms a Hybrid Software-Defined Network (HSDN). Software-Defined Network Frameworks: Security Issues and Use Cases consolidates the research relating to the security in SDN, CSDN, and Hybrid SDNs. The security enhancements derived from the use of various SDN frameworks and the security challenges thus introduced, are also discussed. Overall, this book explains the different architectures of SDNs and the security challenges needed for implementing them.

Features:

  • Illustrates different frameworks of SDN and their security issues in a single volume
  • Discusses design and assessment of efficient SDN northbound/southbound interfaces
  • Describes cognitive computing, affective computing, machine learning, and other novel tools
  • Illustrates coupling of SDN and traditional networking – Hybrid SDN
  • Explores services, technologies, algorithms, and methods for data analysis in CSDN

The book is aimed at researchers and graduate students in software engineering, network security, computer networks, high performance computing, communications engineering, and intelligent systems.

This book consolidates the research relating to the security in SDN, CSDN, and Hybrid SDNs. The security enhancements derived from use of various SDN frameworks and the security challenges thus introduced, are also discussed. Overall, this book explains different architectures of SDNs and the security challenges needs for implementing them.

Software-Defined Networks (SDN) work by virtualization of the network and the Cognitive Software-Defined Network (CSDN) combines the efficiencies of SDN with cognitive learning algorithms and enhanced protocols to automatize SDN. Partial deployment of SDN along with traditional networking devices forms a Hybrid Software-Defined Network (HSDN). Software-Defined Network Frameworks: Security Issues and Use Cases consolidates the research relating to the security in SDN, CSDN, and Hybrid SDNs. The security enhancements derived from the use of various SDN frameworks and the security challenges thus introduced, are also discussed. Overall, this book explains the different architectures of SDNs and the security challenges needed for implementing them.

Features:

  • Illustrates different frameworks of SDN and their security issues in a single volume
  • Discusses design and assessment of efficient SDN northbound/southbound interfaces
  • Describes cognitive computing, affective computing, machine learning, and other novel tools
  • Illustrates coupling of SDN and traditional networking – Hybrid SDN
  • Explores services, technologies, algorithms, and methods for data analysis in CSDN

The book is aimed at researchers and graduate students in software engineering, network security, computer networks, high performance computing, communications engineering, and intelligent systems.

This book consolidates the research relating to the security in SDN, CSDN, and Hybrid SDNs. The security enhancements derived from use of various SDN frameworks and the security challenges thus introduced, are also discussed. Overall, this book explains different architectures of SDNs and the security challenges needs for implementing them.

Software-Defined Networks (SDN) work by virtualization of the network and the Cognitive Software-Defined Network (CSDN) combines the efficiencies of SDN with cognitive learning algorithms and enhanced protocols to automatize SDN. Partial deployment of SDN along with traditional networking devices forms a Hybrid Software-Defined Network (HSDN). Software-Defined Network Frameworks: Security Issues and Use Cases consolidates the research relating to the security in SDN, CSDN, and Hybrid SDNs. The security enhancements derived from the use of various SDN frameworks and the security challenges thus introduced, are also discussed. Overall, this book explains the different architectures of SDNs and the security challenges needed for implementing them.

Features:

  • Illustrates different frameworks of SDN and their security issues in a single volume
  • Discusses design and assessment of efficient SDN northbound/southbound interfaces
  • Describes cognitive computing, affective computing, machine learning, and other novel tools
  • Illustrates coupling of SDN and traditional networking – Hybrid SDN
  • Explores services, technologies, algorithms, and methods for data analysis in CSDN

The book is aimed at researchers and graduate students in software engineering, network security, computer networks, high performance computing, communications engineering, and intelligent systems.

This book consolidates the research relating to the security in SDN, CSDN, and Hybrid SDNs. The security enhancements derived from use of various SDN frameworks and the security challenges thus introduced, are also discussed. Overall, this book explains different architectures of SDNs and the security challenges needs for implementing them.

Software-Defined Networks (SDN) work by virtualization of the network and the Cognitive Software-Defined Network (CSDN) combines the efficiencies of SDN with cognitive learning algorithms and enhanced protocols to automatize SDN. Partial deployment of SDN along with traditional networking devices forms a Hybrid Software-Defined Network (HSDN). Software-Defined Network Frameworks: Security Issues and Use Cases consolidates the research relating to the security in SDN, CSDN, and Hybrid SDNs. The security enhancements derived from the use of various SDN frameworks and the security challenges thus introduced, are also discussed. Overall, this book explains the different architectures of SDNs and the security challenges needed for implementing them.

Features:

  • Illustrates different frameworks of SDN and their security issues in a single volume
  • Discusses design and assessment of efficient SDN northbound/southbound interfaces
  • Describes cognitive computing, affective computing, machine learning, and other novel tools
  • Illustrates coupling of SDN and traditional networking – Hybrid SDN
  • Explores services, technologies, algorithms, and methods for data analysis in CSDN

The book is aimed at researchers and graduate students in software engineering, network security, computer networks, high performance computing, communications engineering, and intelligent systems.

This book consolidates the research relating to the security in SDN, CSDN, and Hybrid SDNs. The security enhancements derived from use of various SDN frameworks and the security challenges thus introduced, are also discussed. Overall, this book explains different architectures of SDNs and the security challenges needs for implementing them.

Software-Defined Networks (SDN) work by virtualization of the network and the Cognitive Software-Defined Network (CSDN) combines the efficiencies of SDN with cognitive learning algorithms and enhanced protocols to automatize SDN. Partial deployment of SDN along with traditional networking devices forms a Hybrid Software-Defined Network (HSDN). Software-Defined Network Frameworks: Security Issues and Use Cases consolidates the research relating to the security in SDN, CSDN, and Hybrid SDNs. The security enhancements derived from the use of various SDN frameworks and the security challenges thus introduced, are also discussed. Overall, this book explains the different architectures of SDNs and the security challenges needed for implementing them.

Features:

  • Illustrates different frameworks of SDN and their security issues in a single volume
  • Discusses design and assessment of efficient SDN northbound/southbound interfaces
  • Describes cognitive computing, affective computing, machine learning, and other novel tools
  • Illustrates coupling of SDN and traditional networking – Hybrid SDN
  • Explores services, technologies, algorithms, and methods for data analysis in CSDN

The book is aimed at researchers and graduate students in software engineering, network security, computer networks, high performance computing, communications engineering, and intelligent systems.

This book consolidates the research relating to the security in SDN, CSDN, and Hybrid SDNs. The security enhancements derived from use of various SDN frameworks and the security challenges thus introduced, are also discussed. Overall, this book explains different architectures of SDNs and the security challenges needs for implementing them.

Software-Defined Networks (SDN) work by virtualization of the network and the Cognitive Software-Defined Network (CSDN) combines the efficiencies of SDN with cognitive learning algorithms and enhanced protocols to automatize SDN. Partial deployment of SDN along with traditional networking devices forms a Hybrid Software-Defined Network (HSDN). Software-Defined Network Frameworks: Security Issues and Use Cases consolidates the research relating to the security in SDN, CSDN, and Hybrid SDNs. The security enhancements derived from the use of various SDN frameworks and the security challenges thus introduced, are also discussed. Overall, this book explains the different architectures of SDNs and the security challenges needed for implementing them.

Features:

  • Illustrates different frameworks of SDN and their security issues in a single volume
  • Discusses design and assessment of efficient SDN northbound/southbound interfaces
  • Describes cognitive computing, affective computing, machine learning, and other novel tools
  • Illustrates coupling of SDN and traditional networking – Hybrid SDN
  • Explores services, technologies, algorithms, and methods for data analysis in CSDN

The book is aimed at researchers and graduate students in software engineering, network security, computer networks, high performance computing, communications engineering, and intelligent systems.

This book consolidates the research relating to the security in SDN, CSDN, and Hybrid SDNs. The security enhancements derived from use of various SDN frameworks and the security challenges thus introduced, are also discussed. Overall, this book explains different architectures of SDNs and the security challenges needs for implementing them.

Software-Defined Networks (SDN) work by virtualization of the network and the Cognitive Software-Defined Network (CSDN) combines the efficiencies of SDN with cognitive learning algorithms and enhanced protocols to automatize SDN. Partial deployment of SDN along with traditional networking devices forms a Hybrid Software-Defined Network (HSDN). Software-Defined Network Frameworks: Security Issues and Use Cases consolidates the research relating to the security in SDN, CSDN, and Hybrid SDNs. The security enhancements derived from the use of various SDN frameworks and the security challenges thus introduced, are also discussed. Overall, this book explains the different architectures of SDNs and the security challenges needed for implementing them.

Features:

  • Illustrates different frameworks of SDN and their security issues in a single volume
  • Discusses design and assessment of efficient SDN northbound/southbound interfaces
  • Describes cognitive computing, affective computing, machine learning, and other novel tools
  • Illustrates coupling of SDN and traditional networking – Hybrid SDN
  • Explores services, technologies, algorithms, and methods for data analysis in CSDN

The book is aimed at researchers and graduate students in software engineering, network security, computer networks, high performance computing, communications engineering, and intelligent systems.

This book consolidates the research relating to the security in SDN, CSDN, and Hybrid SDNs. The security enhancements derived from use of various SDN frameworks and the security challenges thus introduced, are also discussed. Overall, this book explains different architectures of SDNs and the security challenges needs for implementing them.

Software-Defined Networks (SDN) work by virtualization of the network and the Cognitive Software-Defined Network (CSDN) combines the efficiencies of SDN with cognitive learning algorithms and enhanced protocols to automatize SDN. Partial deployment of SDN along with traditional networking devices forms a Hybrid Software-Defined Network (HSDN). Software-Defined Network Frameworks: Security Issues and Use Cases consolidates the research relating to the security in SDN, CSDN, and Hybrid SDNs. The security enhancements derived from the use of various SDN frameworks and the security challenges thus introduced, are also discussed. Overall, this book explains the different architectures of SDNs and the security challenges needed for implementing them.

Features:

  • Illustrates different frameworks of SDN and their security issues in a single volume
  • Discusses design and assessment of efficient SDN northbound/southbound interfaces
  • Describes cognitive computing, affective computing, machine learning, and other novel tools
  • Illustrates coupling of SDN and traditional networking – Hybrid SDN
  • Explores services, technologies, algorithms, and methods for data analysis in CSDN

The book is aimed at researchers and graduate students in software engineering, network security, computer networks, high performance computing, communications engineering, and intelligent systems.

This book consolidates the research relating to the security in SDN, CSDN, and Hybrid SDNs. The security enhancements derived from use of various SDN frameworks and the security challenges thus introduced, are also discussed. Overall, this book explains different architectures of SDNs and the security challenges needs for implementing them.

Software-Defined Networks (SDN) work by virtualization of the network and the Cognitive Software-Defined Network (CSDN) combines the efficiencies of SDN with cognitive learning algorithms and enhanced protocols to automatize SDN. Partial deployment of SDN along with traditional networking devices forms a Hybrid Software-Defined Network (HSDN). Software-Defined Network Frameworks: Security Issues and Use Cases consolidates the research relating to the security in SDN, CSDN, and Hybrid SDNs. The security enhancements derived from the use of various SDN frameworks and the security challenges thus introduced, are also discussed. Overall, this book explains the different architectures of SDNs and the security challenges needed for implementing them.

Features:

  • Illustrates different frameworks of SDN and their security issues in a single volume
  • Discusses design and assessment of efficient SDN northbound/southbound interfaces
  • Describes cognitive computing, affective computing, machine learning, and other novel tools
  • Illustrates coupling of SDN and traditional networking – Hybrid SDN
  • Explores services, technologies, algorithms, and methods for data analysis in CSDN

The book is aimed at researchers and graduate students in software engineering, network security, computer networks, high performance computing, communications engineering, and intelligent systems.

This book consolidates the research relating to the security in SDN, CSDN, and Hybrid SDNs. The security enhancements derived from use of various SDN frameworks and the security challenges thus introduced, are also discussed. Overall, this book explains different architectures of SDNs and the security challenges needs for implementing them.

Software-Defined Networks (SDN) work by virtualization of the network and the Cognitive Software-Defined Network (CSDN) combines the efficiencies of SDN with cognitive learning algorithms and enhanced protocols to automatize SDN. Partial deployment of SDN along with traditional networking devices forms a Hybrid Software-Defined Network (HSDN). Software-Defined Network Frameworks: Security Issues and Use Cases consolidates the research relating to the security in SDN, CSDN, and Hybrid SDNs. The security enhancements derived from the use of various SDN frameworks and the security challenges thus introduced, are also discussed. Overall, this book explains the different architectures of SDNs and the security challenges needed for implementing them.

Features:

  • Illustrates different frameworks of SDN and their security issues in a single volume
  • Discusses design and assessment of efficient SDN northbound/southbound interfaces
  • Describes cognitive computing, affective computing, machine learning, and other novel tools
  • Illustrates coupling of SDN and traditional networking – Hybrid SDN
  • Explores services, technologies, algorithms, and methods for data analysis in CSDN

The book is aimed at researchers and graduate students in software engineering, network security, computer networks, high performance computing, communications engineering, and intelligent systems.

This book consolidates the research relating to the security in SDN, CSDN, and Hybrid SDNs. The security enhancements derived from use of various SDN frameworks and the security challenges thus introduced, are also discussed. Overall, this book explains different architectures of SDNs and the security challenges needs for implementing them.

Software-Defined Networks (SDN) work by virtualization of the network and the Cognitive Software-Defined Network (CSDN) combines the efficiencies of SDN with cognitive learning algorithms and enhanced protocols to automatize SDN. Partial deployment of SDN along with traditional networking devices forms a Hybrid Software-Defined Network (HSDN). Software-Defined Network Frameworks: Security Issues and Use Cases consolidates the research relating to the security in SDN, CSDN, and Hybrid SDNs. The security enhancements derived from the use of various SDN frameworks and the security challenges thus introduced, are also discussed. Overall, this book explains the different architectures of SDNs and the security challenges needed for implementing them.

Features:

  • Illustrates different frameworks of SDN and their security issues in a single volume
  • Discusses design and assessment of efficient SDN northbound/southbound interfaces
  • Describes cognitive computing, affective computing, machine learning, and other novel tools
  • Illustrates coupling of SDN and traditional networking – Hybrid SDN
  • Explores services, technologies, algorithms, and methods for data analysis in CSDN

The book is aimed at researchers and graduate students in software engineering, network security, computer networks, high performance computing, communications engineering, and intelligent systems.

This book consolidates the research relating to the security in SDN, CSDN, and Hybrid SDNs. The security enhancements derived from use of various SDN frameworks and the security challenges thus introduced, are also discussed. Overall, this book explains different architectures of SDNs and the security challenges needs for implementing them.

Software-Defined Networks (SDN) work by virtualization of the network and the Cognitive Software-Defined Network (CSDN) combines the efficiencies of SDN with cognitive learning algorithms and enhanced protocols to automatize SDN. Partial deployment of SDN along with traditional networking devices forms a Hybrid Software-Defined Network (HSDN). Software-Defined Network Frameworks: Security Issues and Use Cases consolidates the research relating to the security in SDN, CSDN, and Hybrid SDNs. The security enhancements derived from the use of various SDN frameworks and the security challenges thus introduced, are also discussed. Overall, this book explains the different architectures of SDNs and the security challenges needed for implementing them.

Features:

  • Illustrates different frameworks of SDN and their security issues in a single volume
  • Discusses design and assessment of efficient SDN northbound/southbound interfaces
  • Describes cognitive computing, affective computing, machine learning, and other novel tools
  • Illustrates coupling of SDN and traditional networking – Hybrid SDN
  • Explores services, technologies, algorithms, and methods for data analysis in CSDN

The book is aimed at researchers and graduate students in software engineering, network security, computer networks, high performance computing, communications engineering, and intelligent systems.

This book consolidates the research relating to the security in SDN, CSDN, and Hybrid SDNs. The security enhancements derived from use of various SDN frameworks and the security challenges thus introduced, are also discussed. Overall, this book explains different architectures of SDNs and the security challenges needs for implementing them.

Software-Defined Networks (SDN) work by virtualization of the network and the Cognitive Software-Defined Network (CSDN) combines the efficiencies of SDN with cognitive learning algorithms and enhanced protocols to automatize SDN. Partial deployment of SDN along with traditional networking devices forms a Hybrid Software-Defined Network (HSDN). Software-Defined Network Frameworks: Security Issues and Use Cases consolidates the research relating to the security in SDN, CSDN, and Hybrid SDNs. The security enhancements derived from the use of various SDN frameworks and the security challenges thus introduced, are also discussed. Overall, this book explains the different architectures of SDNs and the security challenges needed for implementing them.

Features:

  • Illustrates different frameworks of SDN and their security issues in a single volume
  • Discusses design and assessment of efficient SDN northbound/southbound interfaces
  • Describes cognitive computing, affective computing, machine learning, and other novel tools
  • Illustrates coupling of SDN and traditional networking – Hybrid SDN
  • Explores services, technologies, algorithms, and methods for data analysis in CSDN

The book is aimed at researchers and graduate students in software engineering, network security, computer networks, high performance computing, communications engineering, and intelligent systems.

This book consolidates the research relating to the security in SDN, CSDN, and Hybrid SDNs. The security enhancements derived from use of various SDN frameworks and the security challenges thus introduced, are also discussed. Overall, this book explains different architectures of SDNs and the security challenges needs for implementing them.

Software-Defined Networks (SDN) work by virtualization of the network and the Cognitive Software-Defined Network (CSDN) combines the efficiencies of SDN with cognitive learning algorithms and enhanced protocols to automatize SDN. Partial deployment of SDN along with traditional networking devices forms a Hybrid Software-Defined Network (HSDN). Software-Defined Network Frameworks: Security Issues and Use Cases consolidates the research relating to the security in SDN, CSDN, and Hybrid SDNs. The security enhancements derived from the use of various SDN frameworks and the security challenges thus introduced, are also discussed. Overall, this book explains the different architectures of SDNs and the security challenges needed for implementing them.

Features:

  • Illustrates different frameworks of SDN and their security issues in a single volume
  • Discusses design and assessment of efficient SDN northbound/southbound interfaces
  • Describes cognitive computing, affective computing, machine learning, and other novel tools
  • Illustrates coupling of SDN and traditional networking – Hybrid SDN
  • Explores services, technologies, algorithms, and methods for data analysis in CSDN

The book is aimed at researchers and graduate students in software engineering, network security, computer networks, high performance computing, communications engineering, and intelligent systems.

This book consolidates the research relating to the security in SDN, CSDN, and Hybrid SDNs. The security enhancements derived from use of various SDN frameworks and the security challenges thus introduced, are also discussed. Overall, this book explains different architectures of SDNs and the security challenges needs for implementing them.

Software-Defined Networks (SDN) work by virtualization of the network and the Cognitive Software-Defined Network (CSDN) combines the efficiencies of SDN with cognitive learning algorithms and enhanced protocols to automatize SDN. Partial deployment of SDN along with traditional networking devices forms a Hybrid Software-Defined Network (HSDN). Software-Defined Network Frameworks: Security Issues and Use Cases consolidates the research relating to the security in SDN, CSDN, and Hybrid SDNs. The security enhancements derived from the use of various SDN frameworks and the security challenges thus introduced, are also discussed. Overall, this book explains the different architectures of SDNs and the security challenges needed for implementing them.

Features:

  • Illustrates different frameworks of SDN and their security issues in a single volume
  • Discusses design and assessment of efficient SDN northbound/southbound interfaces
  • Describes cognitive computing, affective computing, machine learning, and other novel tools
  • Illustrates coupling of SDN and traditional networking – Hybrid SDN
  • Explores services, technologies, algorithms, and methods for data analysis in CSDN

The book is aimed at researchers and graduate students in software engineering, network security, computer networks, high performance computing, communications engineering, and intelligent systems.

This book consolidates the research relating to the security in SDN, CSDN, and Hybrid SDNs. The security enhancements derived from use of various SDN frameworks and the security challenges thus introduced, are also discussed. Overall, this book explains different architectures of SDNs and the security challenges needs for implementing them.

Software-Defined Networks (SDN) work by virtualization of the network and the Cognitive Software-Defined Network (CSDN) combines the efficiencies of SDN with cognitive learning algorithms and enhanced protocols to automatize SDN. Partial deployment of SDN along with traditional networking devices forms a Hybrid Software-Defined Network (HSDN). Software-Defined Network Frameworks: Security Issues and Use Cases consolidates the research relating to the security in SDN, CSDN, and Hybrid SDNs. The security enhancements derived from the use of various SDN frameworks and the security challenges thus introduced, are also discussed. Overall, this book explains the different architectures of SDNs and the security challenges needed for implementing them.

Features:

  • Illustrates different frameworks of SDN and their security issues in a single volume
  • Discusses design and assessment of efficient SDN northbound/southbound interfaces
  • Describes cognitive computing, affective computing, machine learning, and other novel tools
  • Illustrates coupling of SDN and traditional networking – Hybrid SDN
  • Explores services, technologies, algorithms, and methods for data analysis in CSDN

The book is aimed at researchers and graduate students in software engineering, network security, computer networks, high performance computing, communications engineering, and intelligent systems.

This book consolidates the research relating to the security in SDN, CSDN, and Hybrid SDNs. The security enhancements derived from use of various SDN frameworks and the security challenges thus introduced, are also discussed. Overall, this book explains different architectures of SDNs and the security challenges needs for implementing them.

Software-Defined Networks (SDN) work by virtualization of the network and the Cognitive Software-Defined Network (CSDN) combines the efficiencies of SDN with cognitive learning algorithms and enhanced protocols to automatize SDN. Partial deployment of SDN along with traditional networking devices forms a Hybrid Software-Defined Network (HSDN). Software-Defined Network Frameworks: Security Issues and Use Cases consolidates the research relating to the security in SDN, CSDN, and Hybrid SDNs. The security enhancements derived from the use of various SDN frameworks and the security challenges thus introduced, are also discussed. Overall, this book explains the different architectures of SDNs and the security challenges needed for implementing them.

Features:

  • Illustrates different frameworks of SDN and their security issues in a single volume
  • Discusses design and assessment of efficient SDN northbound/southbound interfaces
  • Describes cognitive computing, affective computing, machine learning, and other novel tools
  • Illustrates coupling of SDN and traditional networking – Hybrid SDN
  • Explores services, technologies, algorithms, and methods for data analysis in CSDN

The book is aimed at researchers and graduate students in software engineering, network security, computer networks, high performance computing, communications engineering, and intelligent systems.

This book consolidates the research relating to the security in SDN, CSDN, and Hybrid SDNs. The security enhancements derived from use of various SDN frameworks and the security challenges thus introduced, are also discussed. Overall, this book explains different architectures of SDNs and the security challenges needs for implementing them.

Software-Defined Networks (SDN) work by virtualization of the network and the Cognitive Software-Defined Network (CSDN) combines the efficiencies of SDN with cognitive learning algorithms and enhanced protocols to automatize SDN. Partial deployment of SDN along with traditional networking devices forms a Hybrid Software-Defined Network (HSDN). Software-Defined Network Frameworks: Security Issues and Use Cases consolidates the research relating to the security in SDN, CSDN, and Hybrid SDNs. The security enhancements derived from the use of various SDN frameworks and the security challenges thus introduced, are also discussed. Overall, this book explains the different architectures of SDNs and the security challenges needed for implementing them.

Features:

  • Illustrates different frameworks of SDN and their security issues in a single volume
  • Discusses design and assessment of efficient SDN northbound/southbound interfaces
  • Describes cognitive computing, affective computing, machine learning, and other novel tools
  • Illustrates coupling of SDN and traditional networking – Hybrid SDN
  • Explores services, technologies, algorithms, and methods for data analysis in CSDN

The book is aimed at researchers and graduate students in software engineering, network security, computer networks, high performance computing, communications engineering, and intelligent systems.

This book consolidates the research relating to the security in SDN, CSDN, and Hybrid SDNs. The security enhancements derived from use of various SDN frameworks and the security challenges thus introduced, are also discussed. Overall, this book explains different architectures of SDNs and the security challenges needs for implementing them.

Software-Defined Networks (SDN) work by virtualization of the network and the Cognitive Software-Defined Network (CSDN) combines the efficiencies of SDN with cognitive learning algorithms and enhanced protocols to automatize SDN. Partial deployment of SDN along with traditional networking devices forms a Hybrid Software-Defined Network (HSDN). Software-Defined Network Frameworks: Security Issues and Use Cases consolidates the research relating to the security in SDN, CSDN, and Hybrid SDNs. The security enhancements derived from the use of various SDN frameworks and the security challenges thus introduced, are also discussed. Overall, this book explains the different architectures of SDNs and the security challenges needed for implementing them.

Features:

  • Illustrates different frameworks of SDN and their security issues in a single volume
  • Discusses design and assessment of efficient SDN northbound/southbound interfaces
  • Describes cognitive computing, affective computing, machine learning, and other novel tools
  • Illustrates coupling of SDN and traditional networking – Hybrid SDN
  • Explores services, technologies, algorithms, and methods for data analysis in CSDN

The book is aimed at researchers and graduate students in software engineering, network security, computer networks, high performance computing, communications engineering, and intelligent systems.

This book consolidates the research relating to the security in SDN, CSDN, and Hybrid SDNs. The security enhancements derived from use of various SDN frameworks and the security challenges thus introduced, are also discussed. Overall, this book explains different architectures of SDNs and the security challenges needs for implementing them.

Software-Defined Networks (SDN) work by virtualization of the network and the Cognitive Software-Defined Network (CSDN) combines the efficiencies of SDN with cognitive learning algorithms and enhanced protocols to automatize SDN. Partial deployment of SDN along with traditional networking devices forms a Hybrid Software-Defined Network (HSDN). Software-Defined Network Frameworks: Security Issues and Use Cases consolidates the research relating to the security in SDN, CSDN, and Hybrid SDNs. The security enhancements derived from the use of various SDN frameworks and the security challenges thus introduced, are also discussed. Overall, this book explains the different architectures of SDNs and the security challenges needed for implementing them.

Features:

  • Illustrates different frameworks of SDN and their security issues in a single volume
  • Discusses design and assessment of efficient SDN northbound/southbound interfaces
  • Describes cognitive computing, affective computing, machine learning, and other novel tools
  • Illustrates coupling of SDN and traditional networking – Hybrid SDN
  • Explores services, technologies, algorithms, and methods for data analysis in CSDN

The book is aimed at researchers and graduate students in software engineering, network security, computer networks, high performance computing, communications engineering, and intelligent systems.

This book consolidates the research relating to the security in SDN, CSDN, and Hybrid SDNs. The security enhancements derived from use of various SDN frameworks and the security challenges thus introduced, are also discussed. Overall, this book explains different architectures of SDNs and the security challenges needs for implementing them.

Software-Defined Networks (SDN) work by virtualization of the network and the Cognitive Software-Defined Network (CSDN) combines the efficiencies of SDN with cognitive learning algorithms and enhanced protocols to automatize SDN. Partial deployment of SDN along with traditional networking devices forms a Hybrid Software-Defined Network (HSDN). Software-Defined Network Frameworks: Security Issues and Use Cases consolidates the research relating to the security in SDN, CSDN, and Hybrid SDNs. The security enhancements derived from the use of various SDN frameworks and the security challenges thus introduced, are also discussed. Overall, this book explains the different architectures of SDNs and the security challenges needed for implementing them.

Features:

  • Illustrates different frameworks of SDN and their security issues in a single volume
  • Discusses design and assessment of efficient SDN northbound/southbound interfaces
  • Describes cognitive computing, affective computing, machine learning, and other novel tools
  • Illustrates coupling of SDN and traditional networking – Hybrid SDN
  • Explores services, technologies, algorithms, and methods for data analysis in CSDN

The book is aimed at researchers and graduate students in software engineering, network security, computer networks, high performance computing, communications engineering, and intelligent systems.

This book consolidates the research relating to the security in SDN, CSDN, and Hybrid SDNs. The security enhancements derived from use of various SDN frameworks and the security challenges thus introduced, are also discussed. Overall, this book explains different architectures of SDNs and the security challenges needs for implementing them.

Software-Defined Networks (SDN) work by virtualization of the network and the Cognitive Software-Defined Network (CSDN) combines the efficiencies of SDN with cognitive learning algorithms and enhanced protocols to automatize SDN. Partial deployment of SDN along with traditional networking devices forms a Hybrid Software-Defined Network (HSDN). Software-Defined Network Frameworks: Security Issues and Use Cases consolidates the research relating to the security in SDN, CSDN, and Hybrid SDNs. The security enhancements derived from the use of various SDN frameworks and the security challenges thus introduced, are also discussed. Overall, this book explains the different architectures of SDNs and the security challenges needed for implementing them.

Features:

  • Illustrates different frameworks of SDN and their security issues in a single volume
  • Discusses design and assessment of efficient SDN northbound/southbound interfaces
  • Describes cognitive computing, affective computing, machine learning, and other novel tools
  • Illustrates coupling of SDN and traditional networking – Hybrid SDN
  • Explores services, technologies, algorithms, and methods for data analysis in CSDN

The book is aimed at researchers and graduate students in software engineering, network security, computer networks, high performance computing, communications engineering, and intelligent systems.

This book consolidates the research relating to the security in SDN, CSDN, and Hybrid SDNs. The security enhancements derived from use of various SDN frameworks and the security challenges thus introduced, are also discussed. Overall, this book explains different architectures of SDNs and the security challenges needs for implementing them.

Software-Defined Networks (SDN) work by virtualization of the network and the Cognitive Software-Defined Network (CSDN) combines the efficiencies of SDN with cognitive learning algorithms and enhanced protocols to automatize SDN. Partial deployment of SDN along with traditional networking devices forms a Hybrid Software-Defined Network (HSDN). Software-Defined Network Frameworks: Security Issues and Use Cases consolidates the research relating to the security in SDN, CSDN, and Hybrid SDNs. The security enhancements derived from the use of various SDN frameworks and the security challenges thus introduced, are also discussed. Overall, this book explains the different architectures of SDNs and the security challenges needed for implementing them.

Features:

  • Illustrates different frameworks of SDN and their security issues in a single volume
  • Discusses design and assessment of efficient SDN northbound/southbound interfaces
  • Describes cognitive computing, affective computing, machine learning, and other novel tools
  • Illustrates coupling of SDN and traditional networking – Hybrid SDN
  • Explores services, technologies, algorithms, and methods for data analysis in CSDN

The book is aimed at researchers and graduate students in software engineering, network security, computer networks, high performance computing, communications engineering, and intelligent systems.

This book consolidates the research relating to the security in SDN, CSDN, and Hybrid SDNs. The security enhancements derived from use of various SDN frameworks and the security challenges thus introduced, are also discussed. Overall, this book explains different architectures of SDNs and the security challenges needs for implementing them.

Software-Defined Networks (SDN) work by virtualization of the network and the Cognitive Software-Defined Network (CSDN) combines the efficiencies of SDN with cognitive learning algorithms and enhanced protocols to automatize SDN. Partial deployment of SDN along with traditional networking devices forms a Hybrid Software-Defined Network (HSDN). Software-Defined Network Frameworks: Security Issues and Use Cases consolidates the research relating to the security in SDN, CSDN, and Hybrid SDNs. The security enhancements derived from the use of various SDN frameworks and the security challenges thus introduced, are also discussed. Overall, this book explains the different architectures of SDNs and the security challenges needed for implementing them.

Features:

  • Illustrates different frameworks of SDN and their security issues in a single volume
  • Discusses design and assessment of efficient SDN northbound/southbound interfaces
  • Describes cognitive computing, affective computing, machine learning, and other novel tools
  • Illustrates coupling of SDN and traditional networking – Hybrid SDN
  • Explores services, technologies, algorithms, and methods for data analysis in CSDN

The book is aimed at researchers and graduate students in software engineering, network security, computer networks, high performance computing, communications engineering, and intelligent systems.

This book consolidates the research relating to the security in SDN, CSDN, and Hybrid SDNs. The security enhancements derived from use of various SDN frameworks and the security challenges thus introduced, are also discussed. Overall, this book explains different architectures of SDNs and the security challenges needs for implementing them.

Software-Defined Networks (SDN) work by virtualization of the network and the Cognitive Software-Defined Network (CSDN) combines the efficiencies of SDN with cognitive learning algorithms and enhanced protocols to automatize SDN. Partial deployment of SDN along with traditional networking devices forms a Hybrid Software-Defined Network (HSDN). Software-Defined Network Frameworks: Security Issues and Use Cases consolidates the research relating to the security in SDN, CSDN, and Hybrid SDNs. The security enhancements derived from the use of various SDN frameworks and the security challenges thus introduced, are also discussed. Overall, this book explains the different architectures of SDNs and the security challenges needed for implementing them.

Features:

  • Illustrates different frameworks of SDN and their security issues in a single volume
  • Discusses design and assessment of efficient SDN northbound/southbound interfaces
  • Describes cognitive computing, affective computing, machine learning, and other novel tools
  • Illustrates coupling of SDN and traditional networking – Hybrid SDN
  • Explores services, technologies, algorithms, and methods for data analysis in CSDN

The book is aimed at researchers and graduate students in software engineering, network security, computer networks, high performance computing, communications engineering, and intelligent systems.

This book consolidates the research relating to the security in SDN, CSDN, and Hybrid SDNs. The security enhancements derived from use of various SDN frameworks and the security challenges thus introduced, are also discussed. Overall, this book explains different architectures of SDNs and the security challenges needs for implementing them.

Software-Defined Networks (SDN) work by virtualization of the network and the Cognitive Software-Defined Network (CSDN) combines the efficiencies of SDN with cognitive learning algorithms and enhanced protocols to automatize SDN. Partial deployment of SDN along with traditional networking devices forms a Hybrid Software-Defined Network (HSDN). Software-Defined Network Frameworks: Security Issues and Use Cases consolidates the research relating to the security in SDN, CSDN, and Hybrid SDNs. The security enhancements derived from the use of various SDN frameworks and the security challenges thus introduced, are also discussed. Overall, this book explains the different architectures of SDNs and the security challenges needed for implementing them.

Features:

  • Illustrates different frameworks of SDN and their security issues in a single volume
  • Discusses design and assessment of efficient SDN northbound/southbound interfaces
  • Describes cognitive computing, affective computing, machine learning, and other novel tools
  • Illustrates coupling of SDN and traditional networking – Hybrid SDN
  • Explores services, technologies, algorithms, and methods for data analysis in CSDN

The book is aimed at researchers and graduate students in software engineering, network security, computer networks, high performance computing, communications engineering, and intelligent systems.

This book consolidates the research relating to the security in SDN, CSDN, and Hybrid SDNs. The security enhancements derived from use of various SDN frameworks and the security challenges thus introduced, are also discussed. Overall, this book explains different architectures of SDNs and the security challenges needs for implementing them.

Software-Defined Networks (SDN) work by virtualization of the network and the Cognitive Software-Defined Network (CSDN) combines the efficiencies of SDN with cognitive learning algorithms and enhanced protocols to automatize SDN. Partial deployment of SDN along with traditional networking devices forms a Hybrid Software-Defined Network (HSDN). Software-Defined Network Frameworks: Security Issues and Use Cases consolidates the research relating to the security in SDN, CSDN, and Hybrid SDNs. The security enhancements derived from the use of various SDN frameworks and the security challenges thus introduced, are also discussed. Overall, this book explains the different architectures of SDNs and the security challenges needed for implementing them.

Features:

  • Illustrates different frameworks of SDN and their security issues in a single volume
  • Discusses design and assessment of efficient SDN northbound/southbound interfaces
  • Describes cognitive computing, affective computing, machine learning, and other novel tools
  • Illustrates coupling of SDN and traditional networking – Hybrid SDN
  • Explores services, technologies, algorithms, and methods for data analysis in CSDN

The book is aimed at researchers and graduate students in software engineering, network security, computer networks, high performance computing, communications engineering, and intelligent systems.

This book consolidates the research relating to the security in SDN, CSDN, and Hybrid SDNs. The security enhancements derived from use of various SDN frameworks and the security challenges thus introduced, are also discussed. Overall, this book explains different architectures of SDNs and the security challenges needs for implementing them.

Software-Defined Networks (SDN) work by virtualization of the network and the Cognitive Software-Defined Network (CSDN) combines the efficiencies of SDN with cognitive learning algorithms and enhanced protocols to automatize SDN. Partial deployment of SDN along with traditional networking devices forms a Hybrid Software-Defined Network (HSDN). Software-Defined Network Frameworks: Security Issues and Use Cases consolidates the research relating to the security in SDN, CSDN, and Hybrid SDNs. The security enhancements derived from the use of various SDN frameworks and the security challenges thus introduced, are also discussed. Overall, this book explains the different architectures of SDNs and the security challenges needed for implementing them.

Features:

  • Illustrates different frameworks of SDN and their security issues in a single volume
  • Discusses design and assessment of efficient SDN northbound/southbound interfaces
  • Describes cognitive computing, affective computing, machine learning, and other novel tools
  • Illustrates coupling of SDN and traditional networking – Hybrid SDN
  • Explores services, technologies, algorithms, and methods for data analysis in CSDN

The book is aimed at researchers and graduate students in software engineering, network security, computer networks, high performance computing, communications engineering, and intelligent systems.

This book consolidates the research relating to the security in SDN, CSDN, and Hybrid SDNs. The security enhancements derived from use of various SDN frameworks and the security challenges thus introduced, are also discussed. Overall, this book explains different architectures of SDNs and the security challenges needs for implementing them.

Software-Defined Networks (SDN) work by virtualization of the network and the Cognitive Software-Defined Network (CSDN) combines the efficiencies of SDN with cognitive learning algorithms and enhanced protocols to automatize SDN. Partial deployment of SDN along with traditional networking devices forms a Hybrid Software-Defined Network (HSDN). Software-Defined Network Frameworks: Security Issues and Use Cases consolidates the research relating to the security in SDN, CSDN, and Hybrid SDNs. The security enhancements derived from the use of various SDN frameworks and the security challenges thus introduced, are also discussed. Overall, this book explains the different architectures of SDNs and the security challenges needed for implementing them.

Features:

  • Illustrates different frameworks of SDN and their security issues in a single volume
  • Discusses design and assessment of efficient SDN northbound/southbound interfaces
  • Describes cognitive computing, affective computing, machine learning, and other novel tools
  • Illustrates coupling of SDN and traditional networking – Hybrid SDN
  • Explores services, technologies, algorithms, and methods for data analysis in CSDN

The book is aimed at researchers and graduate students in software engineering, network security, computer networks, high performance computing, communications engineering, and intelligent systems.

This book consolidates the research relating to the security in SDN, CSDN, and Hybrid SDNs. The security enhancements derived from use of various SDN frameworks and the security challenges thus introduced, are also discussed. Overall, this book explains different architectures of SDNs and the security challenges needs for implementing them.

Software-Defined Networks (SDN) work by virtualization of the network and the Cognitive Software-Defined Network (CSDN) combines the efficiencies of SDN with cognitive learning algorithms and enhanced protocols to automatize SDN. Partial deployment of SDN along with traditional networking devices forms a Hybrid Software-Defined Network (HSDN). Software-Defined Network Frameworks: Security Issues and Use Cases consolidates the research relating to the security in SDN, CSDN, and Hybrid SDNs. The security enhancements derived from the use of various SDN frameworks and the security challenges thus introduced, are also discussed. Overall, this book explains the different architectures of SDNs and the security challenges needed for implementing them.

Features:

  • Illustrates different frameworks of SDN and their security issues in a single volume
  • Discusses design and assessment of efficient SDN northbound/southbound interfaces
  • Describes cognitive computing, affective computing, machine learning, and other novel tools
  • Illustrates coupling of SDN and traditional networking – Hybrid SDN
  • Explores services, technologies, algorithms, and methods for data analysis in CSDN

The book is aimed at researchers and graduate students in software engineering, network security, computer networks, high performance computing, communications engineering, and intelligent systems.

This book consolidates the research relating to the security in SDN, CSDN, and Hybrid SDNs. The security enhancements derived from use of various SDN frameworks and the security challenges thus introduced, are also discussed. Overall, this book explains different architectures of SDNs and the security challenges needs for implementing them.

Software-Defined Networks (SDN) work by virtualization of the network and the Cognitive Software-Defined Network (CSDN) combines the efficiencies of SDN with cognitive learning algorithms and enhanced protocols to automatize SDN. Partial deployment of SDN along with traditional networking devices forms a Hybrid Software-Defined Network (HSDN). Software-Defined Network Frameworks: Security Issues and Use Cases consolidates the research relating to the security in SDN, CSDN, and Hybrid SDNs. The security enhancements derived from the use of various SDN frameworks and the security challenges thus introduced, are also discussed. Overall, this book explains the different architectures of SDNs and the security challenges needed for implementing them.

Features:

  • Illustrates different frameworks of SDN and their security issues in a single volume
  • Discusses design and assessment of efficient SDN northbound/southbound interfaces
  • Describes cognitive computing, affective computing, machine learning, and other novel tools
  • Illustrates coupling of SDN and traditional networking – Hybrid SDN
  • Explores services, technologies, algorithms, and methods for data analysis in CSDN

The book is aimed at researchers and graduate students in software engineering, network security, computer networks, high performance computing, communications engineering, and intelligent systems.

This book consolidates the research relating to the security in SDN, CSDN, and Hybrid SDNs. The security enhancements derived from use of various SDN frameworks and the security challenges thus introduced, are also discussed. Overall, this book explains different architectures of SDNs and the security challenges needs for implementing them.

Software-Defined Networks (SDN) work by virtualization of the network and the Cognitive Software-Defined Network (CSDN) combines the efficiencies of SDN with cognitive learning algorithms and enhanced protocols to automatize SDN. Partial deployment of SDN along with traditional networking devices forms a Hybrid Software-Defined Network (HSDN). Software-Defined Network Frameworks: Security Issues and Use Cases consolidates the research relating to the security in SDN, CSDN, and Hybrid SDNs. The security enhancements derived from the use of various SDN frameworks and the security challenges thus introduced, are also discussed. Overall, this book explains the different architectures of SDNs and the security challenges needed for implementing them.

Features:

  • Illustrates different frameworks of SDN and their security issues in a single volume
  • Discusses design and assessment of efficient SDN northbound/southbound interfaces
  • Describes cognitive computing, affective computing, machine learning, and other novel tools
  • Illustrates coupling of SDN and traditional networking – Hybrid SDN
  • Explores services, technologies, algorithms, and methods for data analysis in CSDN

The book is aimed at researchers and graduate students in software engineering, network security, computer networks, high performance computing, communications engineering, and intelligent systems.

This book consolidates the research relating to the security in SDN, CSDN, and Hybrid SDNs. The security enhancements derived from use of various SDN frameworks and the security challenges thus introduced, are also discussed. Overall, this book explains different architectures of SDNs and the security challenges needs for implementing them.

Software-Defined Networks (SDN) work by virtualization of the network and the Cognitive Software-Defined Network (CSDN) combines the efficiencies of SDN with cognitive learning algorithms and enhanced protocols to automatize SDN. Partial deployment of SDN along with traditional networking devices forms a Hybrid Software-Defined Network (HSDN). Software-Defined Network Frameworks: Security Issues and Use Cases consolidates the research relating to the security in SDN, CSDN, and Hybrid SDNs. The security enhancements derived from the use of various SDN frameworks and the security challenges thus introduced, are also discussed. Overall, this book explains the different architectures of SDNs and the security challenges needed for implementing them.

Features:

  • Illustrates different frameworks of SDN and their security issues in a single volume
  • Discusses design and assessment of efficient SDN northbound/southbound interfaces
  • Describes cognitive computing, affective computing, machine learning, and other novel tools
  • Illustrates coupling of SDN and traditional networking – Hybrid SDN
  • Explores services, technologies, algorithms, and methods for data analysis in CSDN

The book is aimed at researchers and graduate students in software engineering, network security, computer networks, high performance computing, communications engineering, and intelligent systems.

This book consolidates the research relating to the security in SDN, CSDN, and Hybrid SDNs. The security enhancements derived from use of various SDN frameworks and the security challenges thus introduced, are also discussed. Overall, this book explains different architectures of SDNs and the security challenges needs for implementing them.

Software-Defined Networks (SDN) work by virtualization of the network and the Cognitive Software-Defined Network (CSDN) combines the efficiencies of SDN with cognitive learning algorithms and enhanced protocols to automatize SDN. Partial deployment of SDN along with traditional networking devices forms a Hybrid Software-Defined Network (HSDN). Software-Defined Network Frameworks: Security Issues and Use Cases consolidates the research relating to the security in SDN, CSDN, and Hybrid SDNs. The security enhancements derived from the use of various SDN frameworks and the security challenges thus introduced, are also discussed. Overall, this book explains the different architectures of SDNs and the security challenges needed for implementing them.

Features:

  • Illustrates different frameworks of SDN and their security issues in a single volume
  • Discusses design and assessment of efficient SDN northbound/southbound interfaces
  • Describes cognitive computing, affective computing, machine learning, and other novel tools
  • Illustrates coupling of SDN and traditional networking – Hybrid SDN
  • Explores services, technologies, algorithms, and methods for data analysis in CSDN

The book is aimed at researchers and graduate students in software engineering, network security, computer networks, high performance computing, communications engineering, and intelligent systems.

This book consolidates the research relating to the security in SDN, CSDN, and Hybrid SDNs. The security enhancements derived from use of various SDN frameworks and the security challenges thus introduced, are also discussed. Overall, this book explains different architectures of SDNs and the security challenges needs for implementing them.

Software-Defined Networks (SDN) work by virtualization of the network and the Cognitive Software-Defined Network (CSDN) combines the efficiencies of SDN with cognitive learning algorithms and enhanced protocols to automatize SDN. Partial deployment of SDN along with traditional networking devices forms a Hybrid Software-Defined Network (HSDN). Software-Defined Network Frameworks: Security Issues and Use Cases consolidates the research relating to the security in SDN, CSDN, and Hybrid SDNs. The security enhancements derived from the use of various SDN frameworks and the security challenges thus introduced, are also discussed. Overall, this book explains the different architectures of SDNs and the security challenges needed for implementing them.

Features:

  • Illustrates different frameworks of SDN and their security issues in a single volume
  • Discusses design and assessment of efficient SDN northbound/southbound interfaces
  • Describes cognitive computing, affective computing, machine learning, and other novel tools
  • Illustrates coupling of SDN and traditional networking – Hybrid SDN
  • Explores services, technologies, algorithms, and methods for data analysis in CSDN

The book is aimed at researchers and graduate students in software engineering, network security, computer networks, high performance computing, communications engineering, and intelligent systems.

This book consolidates the research relating to the security in SDN, CSDN, and Hybrid SDNs. The security enhancements derived from use of various SDN frameworks and the security challenges thus introduced, are also discussed. Overall, this book explains different architectures of SDNs and the security challenges needs for implementing them.

Software-Defined Networks (SDN) work by virtualization of the network and the Cognitive Software-Defined Network (CSDN) combines the efficiencies of SDN with cognitive learning algorithms and enhanced protocols to automatize SDN. Partial deployment of SDN along with traditional networking devices forms a Hybrid Software-Defined Network (HSDN). Software-Defined Network Frameworks: Security Issues and Use Cases consolidates the research relating to the security in SDN, CSDN, and Hybrid SDNs. The security enhancements derived from the use of various SDN frameworks and the security challenges thus introduced, are also discussed. Overall, this book explains the different architectures of SDNs and the security challenges needed for implementing them.

Features:

  • Illustrates different frameworks of SDN and their security issues in a single volume
  • Discusses design and assessment of efficient SDN northbound/southbound interfaces
  • Describes cognitive computing, affective computing, machine learning, and other novel tools
  • Illustrates coupling of SDN and traditional networking – Hybrid SDN
  • Explores services, technologies, algorithms, and methods for data analysis in CSDN

The book is aimed at researchers and graduate students in software engineering, network security, computer networks, high performance computing, communications engineering, and intelligent systems.

This book consolidates the research relating to the security in SDN, CSDN, and Hybrid SDNs. The security enhancements derived from use of various SDN frameworks and the security challenges thus introduced, are also discussed. Overall, this book explains different architectures of SDNs and the security challenges needs for implementing them.

Software-Defined Networks (SDN) work by virtualization of the network and the Cognitive Software-Defined Network (CSDN) combines the efficiencies of SDN with cognitive learning algorithms and enhanced protocols to automatize SDN. Partial deployment of SDN along with traditional networking devices forms a Hybrid Software-Defined Network (HSDN). Software-Defined Network Frameworks: Security Issues and Use Cases consolidates the research relating to the security in SDN, CSDN, and Hybrid SDNs. The security enhancements derived from the use of various SDN frameworks and the security challenges thus introduced, are also discussed. Overall, this book explains the different architectures of SDNs and the security challenges needed for implementing them.

Features:

  • Illustrates different frameworks of SDN and their security issues in a single volume
  • Discusses design and assessment of efficient SDN northbound/southbound interfaces
  • Describes cognitive computing, affective computing, machine learning, and other novel tools
  • Illustrates coupling of SDN and traditional networking – Hybrid SDN
  • Explores services, technologies, algorithms, and methods for data analysis in CSDN

The book is aimed at researchers and graduate students in software engineering, network security, computer networks, high performance computing, communications engineering, and intelligent systems.

This book consolidates the research relating to the security in SDN, CSDN, and Hybrid SDNs. The security enhancements derived from use of various SDN frameworks and the security challenges thus introduced, are also discussed. Overall, this book explains different architectures of SDNs and the security challenges needs for implementing them.

Software-Defined Networks (SDN) work by virtualization of the network and the Cognitive Software-Defined Network (CSDN) combines the efficiencies of SDN with cognitive learning algorithms and enhanced protocols to automatize SDN. Partial deployment of SDN along with traditional networking devices forms a Hybrid Software-Defined Network (HSDN). Software-Defined Network Frameworks: Security Issues and Use Cases consolidates the research relating to the security in SDN, CSDN, and Hybrid SDNs. The security enhancements derived from the use of various SDN frameworks and the security challenges thus introduced, are also discussed. Overall, this book explains the different architectures of SDNs and the security challenges needed for implementing them.

Features:

  • Illustrates different frameworks of SDN and their security issues in a single volume
  • Discusses design and assessment of efficient SDN northbound/southbound interfaces
  • Describes cognitive computing, affective computing, machine learning, and other novel tools
  • Illustrates coupling of SDN and traditional networking – Hybrid SDN
  • Explores services, technologies, algorithms, and methods for data analysis in CSDN

The book is aimed at researchers and graduate students in software engineering, network security, computer networks, high performance computing, communications engineering, and intelligent systems.

This book consolidates the research relating to the security in SDN, CSDN, and Hybrid SDNs. The security enhancements derived from use of various SDN frameworks and the security challenges thus introduced, are also discussed. Overall, this book explains different architectures of SDNs and the security challenges needs for implementing them.

Software-Defined Networks (SDN) work by virtualization of the network and the Cognitive Software-Defined Network (CSDN) combines the efficiencies of SDN with cognitive learning algorithms and enhanced protocols to automatize SDN. Partial deployment of SDN along with traditional networking devices forms a Hybrid Software-Defined Network (HSDN). Software-Defined Network Frameworks: Security Issues and Use Cases consolidates the research relating to the security in SDN, CSDN, and Hybrid SDNs. The security enhancements derived from the use of various SDN frameworks and the security challenges thus introduced, are also discussed. Overall, this book explains the different architectures of SDNs and the security challenges needed for implementing them.

Features:

  • Illustrates different frameworks of SDN and their security issues in a single volume
  • Discusses design and assessment of efficient SDN northbound/southbound interfaces
  • Describes cognitive computing, affective computing, machine learning, and other novel tools
  • Illustrates coupling of SDN and traditional networking – Hybrid SDN
  • Explores services, technologies, algorithms, and methods for data analysis in CSDN

The book is aimed at researchers and graduate students in software engineering, network security, computer networks, high performance computing, communications engineering, and intelligent systems.

This book consolidates the research relating to the security in SDN, CSDN, and Hybrid SDNs. The security enhancements derived from use of various SDN frameworks and the security challenges thus introduced, are also discussed. Overall, this book explains different architectures of SDNs and the security challenges needs for implementing them.

Software-Defined Networks (SDN) work by virtualization of the network and the Cognitive Software-Defined Network (CSDN) combines the efficiencies of SDN with cognitive learning algorithms and enhanced protocols to automatize SDN. Partial deployment of SDN along with traditional networking devices forms a Hybrid Software-Defined Network (HSDN). Software-Defined Network Frameworks: Security Issues and Use Cases consolidates the research relating to the security in SDN, CSDN, and Hybrid SDNs. The security enhancements derived from the use of various SDN frameworks and the security challenges thus introduced, are also discussed. Overall, this book explains the different architectures of SDNs and the security challenges needed for implementing them.

Features:

  • Illustrates different frameworks of SDN and their security issues in a single volume
  • Discusses design and assessment of efficient SDN northbound/southbound interfaces
  • Describes cognitive computing, affective computing, machine learning, and other novel tools
  • Illustrates coupling of SDN and traditional networking – Hybrid SDN
  • Explores services, technologies, algorithms, and methods for data analysis in CSDN

The book is aimed at researchers and graduate students in software engineering, network security, computer networks, high performance computing, communications engineering, and intelligent systems.

This book consolidates the research relating to the security in SDN, CSDN, and Hybrid SDNs. The security enhancements derived from use of various SDN frameworks and the security challenges thus introduced, are also discussed. Overall, this book explains different architectures of SDNs and the security challenges needs for implementing them.

Software-Defined Networks (SDN) work by virtualization of the network and the Cognitive Software-Defined Network (CSDN) combines the efficiencies of SDN with cognitive learning algorithms and enhanced protocols to automatize SDN. Partial deployment of SDN along with traditional networking devices forms a Hybrid Software-Defined Network (HSDN). Software-Defined Network Frameworks: Security Issues and Use Cases consolidates the research relating to the security in SDN, CSDN, and Hybrid SDNs. The security enhancements derived from the use of various SDN frameworks and the security challenges thus introduced, are also discussed. Overall, this book explains the different architectures of SDNs and the security challenges needed for implementing them.

Features:

  • Illustrates different frameworks of SDN and their security issues in a single volume
  • Discusses design and assessment of efficient SDN northbound/southbound interfaces
  • Describes cognitive computing, affective computing, machine learning, and other novel tools
  • Illustrates coupling of SDN and traditional networking – Hybrid SDN
  • Explores services, technologies, algorithms, and methods for data analysis in CSDN

The book is aimed at researchers and graduate students in software engineering, network security, computer networks, high performance computing, communications engineering, and intelligent systems.

This book consolidates the research relating to the security in SDN, CSDN, and Hybrid SDNs. The security enhancements derived from use of various SDN frameworks and the security challenges thus introduced, are also discussed. Overall, this book explains different architectures of SDNs and the security challenges needs for implementing them.

Software-Defined Networks (SDN) work by virtualization of the network and the Cognitive Software-Defined Network (CSDN) combines the efficiencies of SDN with cognitive learning algorithms and enhanced protocols to automatize SDN. Partial deployment of SDN along with traditional networking devices forms a Hybrid Software-Defined Network (HSDN). Software-Defined Network Frameworks: Security Issues and Use Cases consolidates the research relating to the security in SDN, CSDN, and Hybrid SDNs. The security enhancements derived from the use of various SDN frameworks and the security challenges thus introduced, are also discussed. Overall, this book explains the different architectures of SDNs and the security challenges needed for implementing them.

Features:

  • Illustrates different frameworks of SDN and their security issues in a single volume
  • Discusses design and assessment of efficient SDN northbound/southbound interfaces
  • Describes cognitive computing, affective computing, machine learning, and other novel tools
  • Illustrates coupling of SDN and traditional networking – Hybrid SDN
  • Explores services, technologies, algorithms, and methods for data analysis in CSDN

The book is aimed at researchers and graduate students in software engineering, network security, computer networks, high performance computing, communications engineering, and intelligent systems.

This book consolidates the research relating to the security in SDN, CSDN, and Hybrid SDNs. The security enhancements derived from use of various SDN frameworks and the security challenges thus introduced, are also discussed. Overall, this book explains different architectures of SDNs and the security challenges needs for implementing them.

Software-Defined Networks (SDN) work by virtualization of the network and the Cognitive Software-Defined Network (CSDN) combines the efficiencies of SDN with cognitive learning algorithms and enhanced protocols to automatize SDN. Partial deployment of SDN along with traditional networking devices forms a Hybrid Software-Defined Network (HSDN). Software-Defined Network Frameworks: Security Issues and Use Cases consolidates the research relating to the security in SDN, CSDN, and Hybrid SDNs. The security enhancements derived from the use of various SDN frameworks and the security challenges thus introduced, are also discussed. Overall, this book explains the different architectures of SDNs and the security challenges needed for implementing them.

Features:

  • Illustrates different frameworks of SDN and their security issues in a single volume
  • Discusses design and assessment of efficient SDN northbound/southbound interfaces
  • Describes cognitive computing, affective computing, machine learning, and other novel tools
  • Illustrates coupling of SDN and traditional networking – Hybrid SDN
  • Explores services, technologies, algorithms, and methods for data analysis in CSDN

The book is aimed at researchers and graduate students in software engineering, network security, computer networks, high performance computing, communications engineering, and intelligent systems.

This book consolidates the research relating to the security in SDN, CSDN, and Hybrid SDNs. The security enhancements derived from use of various SDN frameworks and the security challenges thus introduced, are also discussed. Overall, this book explains different architectures of SDNs and the security challenges needs for implementing them.

Software-Defined Networks (SDN) work by virtualization of the network and the Cognitive Software-Defined Network (CSDN) combines the efficiencies of SDN with cognitive learning algorithms and enhanced protocols to automatize SDN. Partial deployment of SDN along with traditional networking devices forms a Hybrid Software-Defined Network (HSDN). Software-Defined Network Frameworks: Security Issues and Use Cases consolidates the research relating to the security in SDN, CSDN, and Hybrid SDNs. The security enhancements derived from the use of various SDN frameworks and the security challenges thus introduced, are also discussed. Overall, this book explains the different architectures of SDNs and the security challenges needed for implementing them.

Features:

  • Illustrates different frameworks of SDN and their security issues in a single volume
  • Discusses design and assessment of efficient SDN northbound/southbound interfaces
  • Describes cognitive computing, affective computing, machine learning, and other novel tools
  • Illustrates coupling of SDN and traditional networking – Hybrid SDN
  • Explores services, technologies, algorithms, and methods for data analysis in CSDN

The book is aimed at researchers and graduate students in software engineering, network security, computer networks, high performance computing, communications engineering, and intelligent systems.

This book consolidates the research relating to the security in SDN, CSDN, and Hybrid SDNs. The security enhancements derived from use of various SDN frameworks and the security challenges thus introduced, are also discussed. Overall, this book explains different architectures of SDNs and the security challenges needs for implementing them.

Software-Defined Networks (SDN) work by virtualization of the network and the Cognitive Software-Defined Network (CSDN) combines the efficiencies of SDN with cognitive learning algorithms and enhanced protocols to automatize SDN. Partial deployment of SDN along with traditional networking devices forms a Hybrid Software-Defined Network (HSDN). Software-Defined Network Frameworks: Security Issues and Use Cases consolidates the research relating to the security in SDN, CSDN, and Hybrid SDNs. The security enhancements derived from the use of various SDN frameworks and the security challenges thus introduced, are also discussed. Overall, this book explains the different architectures of SDNs and the security challenges needed for implementing them.

Features:

  • Illustrates different frameworks of SDN and their security issues in a single volume
  • Discusses design and assessment of efficient SDN northbound/southbound interfaces
  • Describes cognitive computing, affective computing, machine learning, and other novel tools
  • Illustrates coupling of SDN and traditional networking – Hybrid SDN
  • Explores services, technologies, algorithms, and methods for data analysis in CSDN

The book is aimed at researchers and graduate students in software engineering, network security, computer networks, high performance computing, communications engineering, and intelligent systems.

This book consolidates the research relating to the security in SDN, CSDN, and Hybrid SDNs. The security enhancements derived from use of various SDN frameworks and the security challenges thus introduced, are also discussed. Overall, this book explains different architectures of SDNs and the security challenges needs for implementing them.

Software-Defined Networks (SDN) work by virtualization of the network and the Cognitive Software-Defined Network (CSDN) combines the efficiencies of SDN with cognitive learning algorithms and enhanced protocols to automatize SDN. Partial deployment of SDN along with traditional networking devices forms a Hybrid Software-Defined Network (HSDN). Software-Defined Network Frameworks: Security Issues and Use Cases consolidates the research relating to the security in SDN, CSDN, and Hybrid SDNs. The security enhancements derived from the use of various SDN frameworks and the security challenges thus introduced, are also discussed. Overall, this book explains the different architectures of SDNs and the security challenges needed for implementing them.

Features:

  • Illustrates different frameworks of SDN and their security issues in a single volume
  • Discusses design and assessment of efficient SDN northbound/southbound interfaces
  • Describes cognitive computing, affective computing, machine learning, and other novel tools
  • Illustrates coupling of SDN and traditional networking – Hybrid SDN
  • Explores services, technologies, algorithms, and methods for data analysis in CSDN

The book is aimed at researchers and graduate students in software engineering, network security, computer networks, high performance computing, communications engineering, and intelligent systems.

This book consolidates the research relating to the security in SDN, CSDN, and Hybrid SDNs. The security enhancements derived from use of various SDN frameworks and the security challenges thus introduced, are also discussed. Overall, this book explains different architectures of SDNs and the security challenges needs for implementing them.

Software-Defined Networks (SDN) work by virtualization of the network and the Cognitive Software-Defined Network (CSDN) combines the efficiencies of SDN with cognitive learning algorithms and enhanced protocols to automatize SDN. Partial deployment of SDN along with traditional networking devices forms a Hybrid Software-Defined Network (HSDN). Software-Defined Network Frameworks: Security Issues and Use Cases consolidates the research relating to the security in SDN, CSDN, and Hybrid SDNs. The security enhancements derived from the use of various SDN frameworks and the security challenges thus introduced, are also discussed. Overall, this book explains the different architectures of SDNs and the security challenges needed for implementing them.

Features:

  • Illustrates different frameworks of SDN and their security issues in a single volume
  • Discusses design and assessment of efficient SDN northbound/southbound interfaces
  • Describes cognitive computing, affective computing, machine learning, and other novel tools
  • Illustrates coupling of SDN and traditional networking – Hybrid SDN
  • Explores services, technologies, algorithms, and methods for data analysis in CSDN

The book is aimed at researchers and graduate students in software engineering, network security, computer networks, high performance computing, communications engineering, and intelligent systems.

This book consolidates the research relating to the security in SDN, CSDN, and Hybrid SDNs. The security enhancements derived from use of various SDN frameworks and the security challenges thus introduced, are also discussed. Overall, this book explains different architectures of SDNs and the security challenges needs for implementing them.

Software-Defined Networks (SDN) work by virtualization of the network and the Cognitive Software-Defined Network (CSDN) combines the efficiencies of SDN with cognitive learning algorithms and enhanced protocols to automatize SDN. Partial deployment of SDN along with traditional networking devices forms a Hybrid Software-Defined Network (HSDN). Software-Defined Network Frameworks: Security Issues and Use Cases consolidates the research relating to the security in SDN, CSDN, and Hybrid SDNs. The security enhancements derived from the use of various SDN frameworks and the security challenges thus introduced, are also discussed. Overall, this book explains the different architectures of SDNs and the security challenges needed for implementing them.

Features:

  • Illustrates different frameworks of SDN and their security issues in a single volume
  • Discusses design and assessment of efficient SDN northbound/southbound interfaces
  • Describes cognitive computing, affective computing, machine learning, and other novel tools
  • Illustrates coupling of SDN and traditional networking – Hybrid SDN
  • Explores services, technologies, algorithms, and methods for data analysis in CSDN

The book is aimed at researchers and graduate students in software engineering, network security, computer networks, high performance computing, communications engineering, and intelligent systems.

This book consolidates the research relating to the security in SDN, CSDN, and Hybrid SDNs. The security enhancements derived from use of various SDN frameworks and the security challenges thus introduced, are also discussed. Overall, this book explains different architectures of SDNs and the security challenges needs for implementing them.

Software-Defined Networks (SDN) work by virtualization of the network and the Cognitive Software-Defined Network (CSDN) combines the efficiencies of SDN with cognitive learning algorithms and enhanced protocols to automatize SDN. Partial deployment of SDN along with traditional networking devices forms a Hybrid Software-Defined Network (HSDN). Software-Defined Network Frameworks: Security Issues and Use Cases consolidates the research relating to the security in SDN, CSDN, and Hybrid SDNs. The security enhancements derived from the use of various SDN frameworks and the security challenges thus introduced, are also discussed. Overall, this book explains the different architectures of SDNs and the security challenges needed for implementing them.

Features:

  • Illustrates different frameworks of SDN and their security issues in a single volume
  • Discusses design and assessment of efficient SDN northbound/southbound interfaces
  • Describes cognitive computing, affective computing, machine learning, and other novel tools
  • Illustrates coupling of SDN and traditional networking – Hybrid SDN
  • Explores services, technologies, algorithms, and methods for data analysis in CSDN

The book is aimed at researchers and graduate students in software engineering, network security, computer networks, high performance computing, communications engineering, and intelligent systems.

This book consolidates the research relating to the security in SDN, CSDN, and Hybrid SDNs. The security enhancements derived from use of various SDN frameworks and the security challenges thus introduced, are also discussed. Overall, this book explains different architectures of SDNs and the security challenges needs for implementing them.

Software-Defined Networks (SDN) work by virtualization of the network and the Cognitive Software-Defined Network (CSDN) combines the efficiencies of SDN with cognitive learning algorithms and enhanced protocols to automatize SDN. Partial deployment of SDN along with traditional networking devices forms a Hybrid Software-Defined Network (HSDN). Software-Defined Network Frameworks: Security Issues and Use Cases consolidates the research relating to the security in SDN, CSDN, and Hybrid SDNs. The security enhancements derived from the use of various SDN frameworks and the security challenges thus introduced, are also discussed. Overall, this book explains the different architectures of SDNs and the security challenges needed for implementing them.

Features:

  • Illustrates different frameworks of SDN and their security issues in a single volume
  • Discusses design and assessment of efficient SDN northbound/southbound interfaces
  • Describes cognitive computing, affective computing, machine learning, and other novel tools
  • Illustrates coupling of SDN and traditional networking – Hybrid SDN
  • Explores services, technologies, algorithms, and methods for data analysis in CSDN

The book is aimed at researchers and graduate students in software engineering, network security, computer networks, high performance computing, communications engineering, and intelligent systems.

This book consolidates the research relating to the security in SDN, CSDN, and Hybrid SDNs. The security enhancements derived from use of various SDN frameworks and the security challenges thus introduced, are also discussed. Overall, this book explains different architectures of SDNs and the security challenges needs for implementing them.

Software-Defined Networks (SDN) work by virtualization of the network and the Cognitive Software-Defined Network (CSDN) combines the efficiencies of SDN with cognitive learning algorithms and enhanced protocols to automatize SDN. Partial deployment of SDN along with traditional networking devices forms a Hybrid Software-Defined Network (HSDN). Software-Defined Network Frameworks: Security Issues and Use Cases consolidates the research relating to the security in SDN, CSDN, and Hybrid SDNs. The security enhancements derived from the use of various SDN frameworks and the security challenges thus introduced, are also discussed. Overall, this book explains the different architectures of SDNs and the security challenges needed for implementing them.

Features:

  • Illustrates different frameworks of SDN and their security issues in a single volume
  • Discusses design and assessment of efficient SDN northbound/southbound interfaces
  • Describes cognitive computing, affective computing, machine learning, and other novel tools
  • Illustrates coupling of SDN and traditional networking – Hybrid SDN
  • Explores services, technologies, algorithms, and methods for data analysis in CSDN

The book is aimed at researchers and graduate students in software engineering, network security, computer networks, high performance computing, communications engineering, and intelligent systems.

This book consolidates the research relating to the security in SDN, CSDN, and Hybrid SDNs. The security enhancements derived from use of various SDN frameworks and the security challenges thus introduced, are also discussed. Overall, this book explains different architectures of SDNs and the security challenges needs for implementing them.

Software-Defined Networks (SDN) work by virtualization of the network and the Cognitive Software-Defined Network (CSDN) combines the efficiencies of SDN with cognitive learning algorithms and enhanced protocols to automatize SDN. Partial deployment of SDN along with traditional networking devices forms a Hybrid Software-Defined Network (HSDN). Software-Defined Network Frameworks: Security Issues and Use Cases consolidates the research relating to the security in SDN, CSDN, and Hybrid SDNs. The security enhancements derived from the use of various SDN frameworks and the security challenges thus introduced, are also discussed. Overall, this book explains the different architectures of SDNs and the security challenges needed for implementing them.

Features:

  • Illustrates different frameworks of SDN and their security issues in a single volume
  • Discusses design and assessment of efficient SDN northbound/southbound interfaces
  • Describes cognitive computing, affective computing, machine learning, and other novel tools
  • Illustrates coupling of SDN and traditional networking – Hybrid SDN
  • Explores services, technologies, algorithms, and methods for data analysis in CSDN

The book is aimed at researchers and graduate students in software engineering, network security, computer networks, high performance computing, communications engineering, and intelligent systems.

This book consolidates the research relating to the security in SDN, CSDN, and Hybrid SDNs. The security enhancements derived from use of various SDN frameworks and the security challenges thus introduced, are also discussed. Overall, this book explains different architectures of SDNs and the security challenges needs for implementing them.

Software-Defined Networks (SDN) work by virtualization of the network and the Cognitive Software-Defined Network (CSDN) combines the efficiencies of SDN with cognitive learning algorithms and enhanced protocols to automatize SDN. Partial deployment of SDN along with traditional networking devices forms a Hybrid Software-Defined Network (HSDN). Software-Defined Network Frameworks: Security Issues and Use Cases consolidates the research relating to the security in SDN, CSDN, and Hybrid SDNs. The security enhancements derived from the use of various SDN frameworks and the security challenges thus introduced, are also discussed. Overall, this book explains the different architectures of SDNs and the security challenges needed for implementing them.

Features:

  • Illustrates different frameworks of SDN and their security issues in a single volume
  • Discusses design and assessment of efficient SDN northbound/southbound interfaces
  • Describes cognitive computing, affective computing, machine learning, and other novel tools
  • Illustrates coupling of SDN and traditional networking – Hybrid SDN
  • Explores services, technologies, algorithms, and methods for data analysis in CSDN

The book is aimed at researchers and graduate students in software engineering, network security, computer networks, high performance computing, communications engineering, and intelligent systems.

This book consolidates the research relating to the security in SDN, CSDN, and Hybrid SDNs. The security enhancements derived from use of various SDN frameworks and the security challenges thus introduced, are also discussed. Overall, this book explains different architectures of SDNs and the security challenges needs for implementing them.

Software-Defined Networks (SDN) work by virtualization of the network and the Cognitive Software-Defined Network (CSDN) combines the efficiencies of SDN with cognitive learning algorithms and enhanced protocols to automatize SDN. Partial deployment of SDN along with traditional networking devices forms a Hybrid Software-Defined Network (HSDN). Software-Defined Network Frameworks: Security Issues and Use Cases consolidates the research relating to the security in SDN, CSDN, and Hybrid SDNs. The security enhancements derived from the use of various SDN frameworks and the security challenges thus introduced, are also discussed. Overall, this book explains the different architectures of SDNs and the security challenges needed for implementing them.

Features:

  • Illustrates different frameworks of SDN and their security issues in a single volume
  • Discusses design and assessment of efficient SDN northbound/southbound interfaces
  • Describes cognitive computing, affective computing, machine learning, and other novel tools
  • Illustrates coupling of SDN and traditional networking – Hybrid SDN
  • Explores services, technologies, algorithms, and methods for data analysis in CSDN

The book is aimed at researchers and graduate students in software engineering, network security, computer networks, high performance computing, communications engineering, and intelligent systems.

This book consolidates the research relating to the security in SDN, CSDN, and Hybrid SDNs. The security enhancements derived from use of various SDN frameworks and the security challenges thus introduced, are also discussed. Overall, this book explains different architectures of SDNs and the security challenges needs for implementing them.

Software-Defined Networks (SDN) work by virtualization of the network and the Cognitive Software-Defined Network (CSDN) combines the efficiencies of SDN with cognitive learning algorithms and enhanced protocols to automatize SDN. Partial deployment of SDN along with traditional networking devices forms a Hybrid Software-Defined Network (HSDN). Software-Defined Network Frameworks: Security Issues and Use Cases consolidates the research relating to the security in SDN, CSDN, and Hybrid SDNs. The security enhancements derived from the use of various SDN frameworks and the security challenges thus introduced, are also discussed. Overall, this book explains the different architectures of SDNs and the security challenges needed for implementing them.

Features:

  • Illustrates different frameworks of SDN and their security issues in a single volume
  • Discusses design and assessment of efficient SDN northbound/southbound interfaces
  • Describes cognitive computing, affective computing, machine learning, and other novel tools
  • Illustrates coupling of SDN and traditional networking – Hybrid SDN
  • Explores services, technologies, algorithms, and methods for data analysis in CSDN

The book is aimed at researchers and graduate students in software engineering, network security, computer networks, high performance computing, communications engineering, and intelligent systems.

This book consolidates the research relating to the security in SDN, CSDN, and Hybrid SDNs. The security enhancements derived from use of various SDN frameworks and the security challenges thus introduced, are also discussed. Overall, this book explains different architectures of SDNs and the security challenges needs for implementing them.

Software-Defined Networks (SDN) work by virtualization of the network and the Cognitive Software-Defined Network (CSDN) combines the efficiencies of SDN with cognitive learning algorithms and enhanced protocols to automatize SDN. Partial deployment of SDN along with traditional networking devices forms a Hybrid Software-Defined Network (HSDN). Software-Defined Network Frameworks: Security Issues and Use Cases consolidates the research relating to the security in SDN, CSDN, and Hybrid SDNs. The security enhancements derived from the use of various SDN frameworks and the security challenges thus introduced, are also discussed. Overall, this book explains the different architectures of SDNs and the security challenges needed for implementing them.

Features:

  • Illustrates different frameworks of SDN and their security issues in a single volume
  • Discusses design and assessment of efficient SDN northbound/southbound interfaces
  • Describes cognitive computing, affective computing, machine learning, and other novel tools
  • Illustrates coupling of SDN and traditional networking – Hybrid SDN
  • Explores services, technologies, algorithms, and methods for data analysis in CSDN

The book is aimed at researchers and graduate students in software engineering, network security, computer networks, high performance computing, communications engineering, and intelligent systems.

This book consolidates the research relating to the security in SDN, CSDN, and Hybrid SDNs. The security enhancements derived from use of various SDN frameworks and the security challenges thus introduced, are also discussed. Overall, this book explains different architectures of SDNs and the security challenges needs for implementing them.

Software-Defined Networks (SDN) work by virtualization of the network and the Cognitive Software-Defined Network (CSDN) combines the efficiencies of SDN with cognitive learning algorithms and enhanced protocols to automatize SDN. Partial deployment of SDN along with traditional networking devices forms a Hybrid Software-Defined Network (HSDN). Software-Defined Network Frameworks: Security Issues and Use Cases consolidates the research relating to the security in SDN, CSDN, and Hybrid SDNs. The security enhancements derived from the use of various SDN frameworks and the security challenges thus introduced, are also discussed. Overall, this book explains the different architectures of SDNs and the security challenges needed for implementing them.

Features:

  • Illustrates different frameworks of SDN and their security issues in a single volume
  • Discusses design and assessment of efficient SDN northbound/southbound interfaces
  • Describes cognitive computing, affective computing, machine learning, and other novel tools
  • Illustrates coupling of SDN and traditional networking – Hybrid SDN
  • Explores services, technologies, algorithms, and methods for data analysis in CSDN

The book is aimed at researchers and graduate students in software engineering, network security, computer networks, high performance computing, communications engineering, and intelligent systems.

This book consolidates the research relating to the security in SDN, CSDN, and Hybrid SDNs. The security enhancements derived from use of various SDN frameworks and the security challenges thus introduced, are also discussed. Overall, this book explains different architectures of SDNs and the security challenges needs for implementing them.

Software-Defined Networks (SDN) work by virtualization of the network and the Cognitive Software-Defined Network (CSDN) combines the efficiencies of SDN with cognitive learning algorithms and enhanced protocols to automatize SDN. Partial deployment of SDN along with traditional networking devices forms a Hybrid Software-Defined Network (HSDN). Software-Defined Network Frameworks: Security Issues and Use Cases consolidates the research relating to the security in SDN, CSDN, and Hybrid SDNs. The security enhancements derived from the use of various SDN frameworks and the security challenges thus introduced, are also discussed. Overall, this book explains the different architectures of SDNs and the security challenges needed for implementing them.

Features:

  • Illustrates different frameworks of SDN and their security issues in a single volume
  • Discusses design and assessment of efficient SDN northbound/southbound interfaces
  • Describes cognitive computing, affective computing, machine learning, and other novel tools
  • Illustrates coupling of SDN and traditional networking – Hybrid SDN
  • Explores services, technologies, algorithms, and methods for data analysis in CSDN

The book is aimed at researchers and graduate students in software engineering, network security, computer networks, high performance computing, communications engineering, and intelligent systems.

This book consolidates the research relating to the security in SDN, CSDN, and Hybrid SDNs. The security enhancements derived from use of various SDN frameworks and the security challenges thus introduced, are also discussed. Overall, this book explains different architectures of SDNs and the security challenges needs for implementing them.

Software-Defined Networks (SDN) work by virtualization of the network and the Cognitive Software-Defined Network (CSDN) combines the efficiencies of SDN with cognitive learning algorithms and enhanced protocols to automatize SDN. Partial deployment of SDN along with traditional networking devices forms a Hybrid Software-Defined Network (HSDN). Software-Defined Network Frameworks: Security Issues and Use Cases consolidates the research relating to the security in SDN, CSDN, and Hybrid SDNs. The security enhancements derived from the use of various SDN frameworks and the security challenges thus introduced, are also discussed. Overall, this book explains the different architectures of SDNs and the security challenges needed for implementing them.

Features:

  • Illustrates different frameworks of SDN and their security issues in a single volume
  • Discusses design and assessment of efficient SDN northbound/southbound interfaces
  • Describes cognitive computing, affective computing, machine learning, and other novel tools
  • Illustrates coupling of SDN and traditional networking – Hybrid SDN
  • Explores services, technologies, algorithms, and methods for data analysis in CSDN

The book is aimed at researchers and graduate students in software engineering, network security, computer networks, high performance computing, communications engineering, and intelligent systems.

This book consolidates the research relating to the security in SDN, CSDN, and Hybrid SDNs. The security enhancements derived from use of various SDN frameworks and the security challenges thus introduced, are also discussed. Overall, this book explains different architectures of SDNs and the security challenges needs for implementing them.

Software-Defined Networks (SDN) work by virtualization of the network and the Cognitive Software-Defined Network (CSDN) combines the efficiencies of SDN with cognitive learning algorithms and enhanced protocols to automatize SDN. Partial deployment of SDN along with traditional networking devices forms a Hybrid Software-Defined Network (HSDN). Software-Defined Network Frameworks: Security Issues and Use Cases consolidates the research relating to the security in SDN, CSDN, and Hybrid SDNs. The security enhancements derived from the use of various SDN frameworks and the security challenges thus introduced, are also discussed. Overall, this book explains the different architectures of SDNs and the security challenges needed for implementing them.

Features:

  • Illustrates different frameworks of SDN and their security issues in a single volume
  • Discusses design and assessment of efficient SDN northbound/southbound interfaces
  • Describes cognitive computing, affective computing, machine learning, and other novel tools
  • Illustrates coupling of SDN and traditional networking – Hybrid SDN
  • Explores services, technologies, algorithms, and methods for data analysis in CSDN

The book is aimed at researchers and graduate students in software engineering, network security, computer networks, high performance computing, communications engineering, and intelligent systems.

This book consolidates the research relating to the security in SDN, CSDN, and Hybrid SDNs. The security enhancements derived from use of various SDN frameworks and the security challenges thus introduced, are also discussed. Overall, this book explains different architectures of SDNs and the security challenges needs for implementing them.

Software-Defined Networks (SDN) work by virtualization of the network and the Cognitive Software-Defined Network (CSDN) combines the efficiencies of SDN with cognitive learning algorithms and enhanced protocols to automatize SDN. Partial deployment of SDN along with traditional networking devices forms a Hybrid Software-Defined Network (HSDN). Software-Defined Network Frameworks: Security Issues and Use Cases consolidates the research relating to the security in SDN, CSDN, and Hybrid SDNs. The security enhancements derived from the use of various SDN frameworks and the security challenges thus introduced, are also discussed. Overall, this book explains the different architectures of SDNs and the security challenges needed for implementing them.

Features:

  • Illustrates different frameworks of SDN and their security issues in a single volume
  • Discusses design and assessment of efficient SDN northbound/southbound interfaces
  • Describes cognitive computing, affective computing, machine learning, and other novel tools
  • Illustrates coupling of SDN and traditional networking – Hybrid SDN
  • Explores services, technologies, algorithms, and methods for data analysis in CSDN

The book is aimed at researchers and graduate students in software engineering, network security, computer networks, high performance computing, communications engineering, and intelligent systems.

This book consolidates the research relating to the security in SDN, CSDN, and Hybrid SDNs. The security enhancements derived from use of various SDN frameworks and the security challenges thus introduced, are also discussed. Overall, this book explains different architectures of SDNs and the security challenges needs for implementing them.

Software-Defined Networks (SDN) work by virtualization of the network and the Cognitive Software-Defined Network (CSDN) combines the efficiencies of SDN with cognitive learning algorithms and enhanced protocols to automatize SDN. Partial deployment of SDN along with traditional networking devices forms a Hybrid Software-Defined Network (HSDN). Software-Defined Network Frameworks: Security Issues and Use Cases consolidates the research relating to the security in SDN, CSDN, and Hybrid SDNs. The security enhancements derived from the use of various SDN frameworks and the security challenges thus introduced, are also discussed. Overall, this book explains the different architectures of SDNs and the security challenges needed for implementing them.

Features:

  • Illustrates different frameworks of SDN and their security issues in a single volume
  • Discusses design and assessment of efficient SDN northbound/southbound interfaces
  • Describes cognitive computing, affective computing, machine learning, and other novel tools
  • Illustrates coupling of SDN and traditional networking – Hybrid SDN
  • Explores services, technologies, algorithms, and methods for data analysis in CSDN

The book is aimed at researchers and graduate students in software engineering, network security, computer networks, high performance computing, communications engineering, and intelligent systems.

This book consolidates the research relating to the security in SDN, CSDN, and Hybrid SDNs. The security enhancements derived from use of various SDN frameworks and the security challenges thus introduced, are also discussed. Overall, this book explains different architectures of SDNs and the security challenges needs for implementing them.

Software-Defined Networks (SDN) work by virtualization of the network and the Cognitive Software-Defined Network (CSDN) combines the efficiencies of SDN with cognitive learning algorithms and enhanced protocols to automatize SDN. Partial deployment of SDN along with traditional networking devices forms a Hybrid Software-Defined Network (HSDN). Software-Defined Network Frameworks: Security Issues and Use Cases consolidates the research relating to the security in SDN, CSDN, and Hybrid SDNs. The security enhancements derived from the use of various SDN frameworks and the security challenges thus introduced, are also discussed. Overall, this book explains the different architectures of SDNs and the security challenges needed for implementing them.

Features:

  • Illustrates different frameworks of SDN and their security issues in a single volume
  • Discusses design and assessment of efficient SDN northbound/southbound interfaces
  • Describes cognitive computing, affective computing, machine learning, and other novel tools
  • Illustrates coupling of SDN and traditional networking – Hybrid SDN
  • Explores services, technologies, algorithms, and methods for data analysis in CSDN

The book is aimed at researchers and graduate students in software engineering, network security, computer networks, high performance computing, communications engineering, and intelligent systems.

This book consolidates the research relating to the security in SDN, CSDN, and Hybrid SDNs. The security enhancements derived from use of various SDN frameworks and the security challenges thus introduced, are also discussed. Overall, this book explains different architectures of SDNs and the security challenges needs for implementing them.

Software-Defined Networks (SDN) work by virtualization of the network and the Cognitive Software-Defined Network (CSDN) combines the efficiencies of SDN with cognitive learning algorithms and enhanced protocols to automatize SDN. Partial deployment of SDN along with traditional networking devices forms a Hybrid Software-Defined Network (HSDN). Software-Defined Network Frameworks: Security Issues and Use Cases consolidates the research relating to the security in SDN, CSDN, and Hybrid SDNs. The security enhancements derived from the use of various SDN frameworks and the security challenges thus introduced, are also discussed. Overall, this book explains the different architectures of SDNs and the security challenges needed for implementing them.

Features:

  • Illustrates different frameworks of SDN and their security issues in a single volume
  • Discusses design and assessment of efficient SDN northbound/southbound interfaces
  • Describes cognitive computing, affective computing, machine learning, and other novel tools
  • Illustrates coupling of SDN and traditional networking – Hybrid SDN
  • Explores services, technologies, algorithms, and methods for data analysis in CSDN

The book is aimed at researchers and graduate students in software engineering, network security, computer networks, high performance computing, communications engineering, and intelligent systems.

This book consolidates the research relating to the security in SDN, CSDN, and Hybrid SDNs. The security enhancements derived from use of various SDN frameworks and the security challenges thus introduced, are also discussed. Overall, this book explains different architectures of SDNs and the security challenges needs for implementing them.

Software-Defined Networks (SDN) work by virtualization of the network and the Cognitive Software-Defined Network (CSDN) combines the efficiencies of SDN with cognitive learning algorithms and enhanced protocols to automatize SDN. Partial deployment of SDN along with traditional networking devices forms a Hybrid Software-Defined Network (HSDN). Software-Defined Network Frameworks: Security Issues and Use Cases consolidates the research relating to the security in SDN, CSDN, and Hybrid SDNs. The security enhancements derived from the use of various SDN frameworks and the security challenges thus introduced, are also discussed. Overall, this book explains the different architectures of SDNs and the security challenges needed for implementing them.

Features:

  • Illustrates different frameworks of SDN and their security issues in a single volume
  • Discusses design and assessment of efficient SDN northbound/southbound interfaces
  • Describes cognitive computing, affective computing, machine learning, and other novel tools
  • Illustrates coupling of SDN and traditional networking – Hybrid SDN
  • Explores services, technologies, algorithms, and methods for data analysis in CSDN

The book is aimed at researchers and graduate students in software engineering, network security, computer networks, high performance computing, communications engineering, and intelligent systems.

This book consolidates the research relating to the security in SDN, CSDN, and Hybrid SDNs. The security enhancements derived from use of various SDN frameworks and the security challenges thus introduced, are also discussed. Overall, this book explains different architectures of SDNs and the security challenges needs for implementing them.

Software-Defined Networks (SDN) work by virtualization of the network and the Cognitive Software-Defined Network (CSDN) combines the efficiencies of SDN with cognitive learning algorithms and enhanced protocols to automatize SDN. Partial deployment of SDN along with traditional networking devices forms a Hybrid Software-Defined Network (HSDN). Software-Defined Network Frameworks: Security Issues and Use Cases consolidates the research relating to the security in SDN, CSDN, and Hybrid SDNs. The security enhancements derived from the use of various SDN frameworks and the security challenges thus introduced, are also discussed. Overall, this book explains the different architectures of SDNs and the security challenges needed for implementing them.

Features:

  • Illustrates different frameworks of SDN and their security issues in a single volume
  • Discusses design and assessment of efficient SDN northbound/southbound interfaces
  • Describes cognitive computing, affective computing, machine learning, and other novel tools
  • Illustrates coupling of SDN and traditional networking – Hybrid SDN
  • Explores services, technologies, algorithms, and methods for data analysis in CSDN

The book is aimed at researchers and graduate students in software engineering, network security, computer networks, high performance computing, communications engineering, and intelligent systems.

This book consolidates the research relating to the security in SDN, CSDN, and Hybrid SDNs. The security enhancements derived from use of various SDN frameworks and the security challenges thus introduced, are also discussed. Overall, this book explains different architectures of SDNs and the security challenges needs for implementing them.

Software-Defined Networks (SDN) work by virtualization of the network and the Cognitive Software-Defined Network (CSDN) combines the efficiencies of SDN with cognitive learning algorithms and enhanced protocols to automatize SDN. Partial deployment of SDN along with traditional networking devices forms a Hybrid Software-Defined Network (HSDN). Software-Defined Network Frameworks: Security Issues and Use Cases consolidates the research relating to the security in SDN, CSDN, and Hybrid SDNs. The security enhancements derived from the use of various SDN frameworks and the security challenges thus introduced, are also discussed. Overall, this book explains the different architectures of SDNs and the security challenges needed for implementing them.

Features:

  • Illustrates different frameworks of SDN and their security issues in a single volume
  • Discusses design and assessment of efficient SDN northbound/southbound interfaces
  • Describes cognitive computing, affective computing, machine learning, and other novel tools
  • Illustrates coupling of SDN and traditional networking – Hybrid SDN
  • Explores services, technologies, algorithms, and methods for data analysis in CSDN

The book is aimed at researchers and graduate students in software engineering, network security, computer networks, high performance computing, communications engineering, and intelligent systems.

This book consolidates the research relating to the security in SDN, CSDN, and Hybrid SDNs. The security enhancements derived from use of various SDN frameworks and the security challenges thus introduced, are also discussed. Overall, this book explains different architectures of SDNs and the security challenges needs for implementing them.

Software-Defined Networks (SDN) work by virtualization of the network and the Cognitive Software-Defined Network (CSDN) combines the efficiencies of SDN with cognitive learning algorithms and enhanced protocols to automatize SDN. Partial deployment of SDN along with traditional networking devices forms a Hybrid Software-Defined Network (HSDN). Software-Defined Network Frameworks: Security Issues and Use Cases consolidates the research relating to the security in SDN, CSDN, and Hybrid SDNs. The security enhancements derived from the use of various SDN frameworks and the security challenges thus introduced, are also discussed. Overall, this book explains the different architectures of SDNs and the security challenges needed for implementing them.

Features:

  • Illustrates different frameworks of SDN and their security issues in a single volume
  • Discusses design and assessment of efficient SDN northbound/southbound interfaces
  • Describes cognitive computing, affective computing, machine learning, and other novel tools
  • Illustrates coupling of SDN and traditional networking – Hybrid SDN
  • Explores services, technologies, algorithms, and methods for data analysis in CSDN

The book is aimed at researchers and graduate students in software engineering, network security, computer networks, high performance computing, communications engineering, and intelligent systems.

This book consolidates the research relating to the security in SDN, CSDN, and Hybrid SDNs. The security enhancements derived from use of various SDN frameworks and the security challenges thus introduced, are also discussed. Overall, this book explains different architectures of SDNs and the security challenges needs for implementing them.

Software-Defined Networks (SDN) work by virtualization of the network and the Cognitive Software-Defined Network (CSDN) combines the efficiencies of SDN with cognitive learning algorithms and enhanced protocols to automatize SDN. Partial deployment of SDN along with traditional networking devices forms a Hybrid Software-Defined Network (HSDN). Software-Defined Network Frameworks: Security Issues and Use Cases consolidates the research relating to the security in SDN, CSDN, and Hybrid SDNs. The security enhancements derived from the use of various SDN frameworks and the security challenges thus introduced, are also discussed. Overall, this book explains the different architectures of SDNs and the security challenges needed for implementing them.

Features:

  • Illustrates different frameworks of SDN and their security issues in a single volume
  • Discusses design and assessment of efficient SDN northbound/southbound interfaces
  • Describes cognitive computing, affective computing, machine learning, and other novel tools
  • Illustrates coupling of SDN and traditional networking – Hybrid SDN
  • Explores services, technologies, algorithms, and methods for data analysis in CSDN

The book is aimed at researchers and graduate students in software engineering, network security, computer networks, high performance computing, communications engineering, and intelligent systems.

This book consolidates the research relating to the security in SDN, CSDN, and Hybrid SDNs. The security enhancements derived from use of various SDN frameworks and the security challenges thus introduced, are also discussed. Overall, this book explains different architectures of SDNs and the security challenges needs for implementing them.

Software-Defined Networks (SDN) work by virtualization of the network and the Cognitive Software-Defined Network (CSDN) combines the efficiencies of SDN with cognitive learning algorithms and enhanced protocols to automatize SDN. Partial deployment of SDN along with traditional networking devices forms a Hybrid Software-Defined Network (HSDN). Software-Defined Network Frameworks: Security Issues and Use Cases consolidates the research relating to the security in SDN, CSDN, and Hybrid SDNs. The security enhancements derived from the use of various SDN frameworks and the security challenges thus introduced, are also discussed. Overall, this book explains the different architectures of SDNs and the security challenges needed for implementing them.

Features:

  • Illustrates different frameworks of SDN and their security issues in a single volume
  • Discusses design and assessment of efficient SDN northbound/southbound interfaces
  • Describes cognitive computing, affective computing, machine learning, and other novel tools
  • Illustrates coupling of SDN and traditional networking – Hybrid SDN
  • Explores services, technologies, algorithms, and methods for data analysis in CSDN

The book is aimed at researchers and graduate students in software engineering, network security, computer networks, high performance computing, communications engineering, and intelligent systems.

This book consolidates the research relating to the security in SDN, CSDN, and Hybrid SDNs. The security enhancements derived from use of various SDN frameworks and the security challenges thus introduced, are also discussed. Overall, this book explains different architectures of SDNs and the security challenges needs for implementing them.

Software-Defined Networks (SDN) work by virtualization of the network and the Cognitive Software-Defined Network (CSDN) combines the efficiencies of SDN with cognitive learning algorithms and enhanced protocols to automatize SDN. Partial deployment of SDN along with traditional networking devices forms a Hybrid Software-Defined Network (HSDN). Software-Defined Network Frameworks: Security Issues and Use Cases consolidates the research relating to the security in SDN, CSDN, and Hybrid SDNs. The security enhancements derived from the use of various SDN frameworks and the security challenges thus introduced, are also discussed. Overall, this book explains the different architectures of SDNs and the security challenges needed for implementing them.

Features:

  • Illustrates different frameworks of SDN and their security issues in a single volume
  • Discusses design and assessment of efficient SDN northbound/southbound interfaces
  • Describes cognitive computing, affective computing, machine learning, and other novel tools
  • Illustrates coupling of SDN and traditional networking – Hybrid SDN
  • Explores services, technologies, algorithms, and methods for data analysis in CSDN

The book is aimed at researchers and graduate students in software engineering, network security, computer networks, high performance computing, communications engineering, and intelligent systems.

This book consolidates the research relating to the security in SDN, CSDN, and Hybrid SDNs. The security enhancements derived from use of various SDN frameworks and the security challenges thus introduced, are also discussed. Overall, this book explains different architectures of SDNs and the security challenges needs for implementing them.

Software-Defined Networks (SDN) work by virtualization of the network and the Cognitive Software-Defined Network (CSDN) combines the efficiencies of SDN with cognitive learning algorithms and enhanced protocols to automatize SDN. Partial deployment of SDN along with traditional networking devices forms a Hybrid Software-Defined Network (HSDN). Software-Defined Network Frameworks: Security Issues and Use Cases consolidates the research relating to the security in SDN, CSDN, and Hybrid SDNs. The security enhancements derived from the use of various SDN frameworks and the security challenges thus introduced, are also discussed. Overall, this book explains the different architectures of SDNs and the security challenges needed for implementing them.

Features:

  • Illustrates different frameworks of SDN and their security issues in a single volume
  • Discusses design and assessment of efficient SDN northbound/southbound interfaces
  • Describes cognitive computing, affective computing, machine learning, and other novel tools
  • Illustrates coupling of SDN and traditional networking – Hybrid SDN
  • Explores services, technologies, algorithms, and methods for data analysis in CSDN

The book is aimed at researchers and graduate students in software engineering, network security, computer networks, high performance computing, communications engineering, and intelligent systems.

This book consolidates the research relating to the security in SDN, CSDN, and Hybrid SDNs. The security enhancements derived from use of various SDN frameworks and the security challenges thus introduced, are also discussed. Overall, this book explains different architectures of SDNs and the security challenges needs for implementing them.

Software-Defined Networks (SDN) work by virtualization of the network and the Cognitive Software-Defined Network (CSDN) combines the efficiencies of SDN with cognitive learning algorithms and enhanced protocols to automatize SDN. Partial deployment of SDN along with traditional networking devices forms a Hybrid Software-Defined Network (HSDN). Software-Defined Network Frameworks: Security Issues and Use Cases consolidates the research relating to the security in SDN, CSDN, and Hybrid SDNs. The security enhancements derived from the use of various SDN frameworks and the security challenges thus introduced, are also discussed. Overall, this book explains the different architectures of SDNs and the security challenges needed for implementing them.

Features:

  • Illustrates different frameworks of SDN and their security issues in a single volume
  • Discusses design and assessment of efficient SDN northbound/southbound interfaces
  • Describes cognitive computing, affective computing, machine learning, and other novel tools
  • Illustrates coupling of SDN and traditional networking – Hybrid SDN
  • Explores services, technologies, algorithms, and methods for data analysis in CSDN

The book is aimed at researchers and graduate students in software engineering, network security, computer networks, high performance computing, communications engineering, and intelligent systems.

This book consolidates the research relating to the security in SDN, CSDN, and Hybrid SDNs. The security enhancements derived from use of various SDN frameworks and the security challenges thus introduced, are also discussed. Overall, this book explains different architectures of SDNs and the security challenges needs for implementing them.

Software-Defined Networks (SDN) work by virtualization of the network and the Cognitive Software-Defined Network (CSDN) combines the efficiencies of SDN with cognitive learning algorithms and enhanced protocols to automatize SDN. Partial deployment of SDN along with traditional networking devices forms a Hybrid Software-Defined Network (HSDN). Software-Defined Network Frameworks: Security Issues and Use Cases consolidates the research relating to the security in SDN, CSDN, and Hybrid SDNs. The security enhancements derived from the use of various SDN frameworks and the security challenges thus introduced, are also discussed. Overall, this book explains the different architectures of SDNs and the security challenges needed for implementing them.

Features:

  • Illustrates different frameworks of SDN and their security issues in a single volume
  • Discusses design and assessment of efficient SDN northbound/southbound interfaces
  • Describes cognitive computing, affective computing, machine learning, and other novel tools
  • Illustrates coupling of SDN and traditional networking – Hybrid SDN
  • Explores services, technologies, algorithms, and methods for data analysis in CSDN

The book is aimed at researchers and graduate students in software engineering, network security, computer networks, high performance computing, communications engineering, and intelligent systems.

This book consolidates the research relating to the security in SDN, CSDN, and Hybrid SDNs. The security enhancements derived from use of various SDN frameworks and the security challenges thus introduced, are also discussed. Overall, this book explains different architectures of SDNs and the security challenges needs for implementing them.

Software-Defined Networks (SDN) work by virtualization of the network and the Cognitive Software-Defined Network (CSDN) combines the efficiencies of SDN with cognitive learning algorithms and enhanced protocols to automatize SDN. Partial deployment of SDN along with traditional networking devices forms a Hybrid Software-Defined Network (HSDN). Software-Defined Network Frameworks: Security Issues and Use Cases consolidates the research relating to the security in SDN, CSDN, and Hybrid SDNs. The security enhancements derived from the use of various SDN frameworks and the security challenges thus introduced, are also discussed. Overall, this book explains the different architectures of SDNs and the security challenges needed for implementing them.

Features:

  • Illustrates different frameworks of SDN and their security issues in a single volume
  • Discusses design and assessment of efficient SDN northbound/southbound interfaces
  • Describes cognitive computing, affective computing, machine learning, and other novel tools
  • Illustrates coupling of SDN and traditional networking – Hybrid SDN
  • Explores services, technologies, algorithms, and methods for data analysis in CSDN

The book is aimed at researchers and graduate students in software engineering, network security, computer networks, high performance computing, communications engineering, and intelligent systems.

This book consolidates the research relating to the security in SDN, CSDN, and Hybrid SDNs. The security enhancements derived from use of various SDN frameworks and the security challenges thus introduced, are also discussed. Overall, this book explains different architectures of SDNs and the security challenges needs for implementing them.

Software-Defined Networks (SDN) work by virtualization of the network and the Cognitive Software-Defined Network (CSDN) combines the efficiencies of SDN with cognitive learning algorithms and enhanced protocols to automatize SDN. Partial deployment of SDN along with traditional networking devices forms a Hybrid Software-Defined Network (HSDN). Software-Defined Network Frameworks: Security Issues and Use Cases consolidates the research relating to the security in SDN, CSDN, and Hybrid SDNs. The security enhancements derived from the use of various SDN frameworks and the security challenges thus introduced, are also discussed. Overall, this book explains the different architectures of SDNs and the security challenges needed for implementing them.

Features:

  • Illustrates different frameworks of SDN and their security issues in a single volume
  • Discusses design and assessment of efficient SDN northbound/southbound interfaces
  • Describes cognitive computing, affective computing, machine learning, and other novel tools
  • Illustrates coupling of SDN and traditional networking – Hybrid SDN
  • Explores services, technologies, algorithms, and methods for data analysis in CSDN

The book is aimed at researchers and graduate students in software engineering, network security, computer networks, high performance computing, communications engineering, and intelligent systems.

This book consolidates the research relating to the security in SDN, CSDN, and Hybrid SDNs. The security enhancements derived from use of various SDN frameworks and the security challenges thus introduced, are also discussed. Overall, this book explains different architectures of SDNs and the security challenges needs for implementing them.

Software-Defined Networks (SDN) work by virtualization of the network and the Cognitive Software-Defined Network (CSDN) combines the efficiencies of SDN with cognitive learning algorithms and enhanced protocols to automatize SDN. Partial deployment of SDN along with traditional networking devices forms a Hybrid Software-Defined Network (HSDN). Software-Defined Network Frameworks: Security Issues and Use Cases consolidates the research relating to the security in SDN, CSDN, and Hybrid SDNs. The security enhancements derived from the use of various SDN frameworks and the security challenges thus introduced, are also discussed. Overall, this book explains the different architectures of SDNs and the security challenges needed for implementing them.

Features:

  • Illustrates different frameworks of SDN and their security issues in a single volume
  • Discusses design and assessment of efficient SDN northbound/southbound interfaces
  • Describes cognitive computing, affective computing, machine learning, and other novel tools
  • Illustrates coupling of SDN and traditional networking – Hybrid SDN
  • Explores services, technologies, algorithms, and methods for data analysis in CSDN

The book is aimed at researchers and graduate students in software engineering, network security, computer networks, high performance computing, communications engineering, and intelligent systems.

This book consolidates the research relating to the security in SDN, CSDN, and Hybrid SDNs. The security enhancements derived from use of various SDN frameworks and the security challenges thus introduced, are also discussed. Overall, this book explains different architectures of SDNs and the security challenges needs for implementing them.

Software-Defined Networks (SDN) work by virtualization of the network and the Cognitive Software-Defined Network (CSDN) combines the efficiencies of SDN with cognitive learning algorithms and enhanced protocols to automatize SDN. Partial deployment of SDN along with traditional networking devices forms a Hybrid Software-Defined Network (HSDN). Software-Defined Network Frameworks: Security Issues and Use Cases consolidates the research relating to the security in SDN, CSDN, and Hybrid SDNs. The security enhancements derived from the use of various SDN frameworks and the security challenges thus introduced, are also discussed. Overall, this book explains the different architectures of SDNs and the security challenges needed for implementing them.

Features:

  • Illustrates different frameworks of SDN and their security issues in a single volume
  • Discusses design and assessment of efficient SDN northbound/southbound interfaces
  • Describes cognitive computing, affective computing, machine learning, and other novel tools
  • Illustrates coupling of SDN and traditional networking – Hybrid SDN
  • Explores services, technologies, algorithms, and methods for data analysis in CSDN

The book is aimed at researchers and graduate students in software engineering, network security, computer networks, high performance computing, communications engineering, and intelligent systems.

This book consolidates the research relating to the security in SDN, CSDN, and Hybrid SDNs. The security enhancements derived from use of various SDN frameworks and the security challenges thus introduced, are also discussed. Overall, this book explains different architectures of SDNs and the security challenges needs for implementing them.

Software-Defined Networks (SDN) work by virtualization of the network and the Cognitive Software-Defined Network (CSDN) combines the efficiencies of SDN with cognitive learning algorithms and enhanced protocols to automatize SDN. Partial deployment of SDN along with traditional networking devices forms a Hybrid Software-Defined Network (HSDN). Software-Defined Network Frameworks: Security Issues and Use Cases consolidates the research relating to the security in SDN, CSDN, and Hybrid SDNs. The security enhancements derived from the use of various SDN frameworks and the security challenges thus introduced, are also discussed. Overall, this book explains the different architectures of SDNs and the security challenges needed for implementing them.

Features:

  • Illustrates different frameworks of SDN and their security issues in a single volume
  • Discusses design and assessment of efficient SDN northbound/southbound interfaces
  • Describes cognitive computing, affective computing, machine learning, and other novel tools
  • Illustrates coupling of SDN and traditional networking – Hybrid SDN
  • Explores services, technologies, algorithms, and methods for data analysis in CSDN

The book is aimed at researchers and graduate students in software engineering, network security, computer networks, high performance computing, communications engineering, and intelligent systems.

This book consolidates the research relating to the security in SDN, CSDN, and Hybrid SDNs. The security enhancements derived from use of various SDN frameworks and the security challenges thus introduced, are also discussed. Overall, this book explains different architectures of SDNs and the security challenges needs for implementing them.

Software-Defined Networks (SDN) work by virtualization of the network and the Cognitive Software-Defined Network (CSDN) combines the efficiencies of SDN with cognitive learning algorithms and enhanced protocols to automatize SDN. Partial deployment of SDN along with traditional networking devices forms a Hybrid Software-Defined Network (HSDN). Software-Defined Network Frameworks: Security Issues and Use Cases consolidates the research relating to the security in SDN, CSDN, and Hybrid SDNs. The security enhancements derived from the use of various SDN frameworks and the security challenges thus introduced, are also discussed. Overall, this book explains the different architectures of SDNs and the security challenges needed for implementing them.

Features:

  • Illustrates different frameworks of SDN and their security issues in a single volume
  • Discusses design and assessment of efficient SDN northbound/southbound interfaces
  • Describes cognitive computing, affective computing, machine learning, and other novel tools
  • Illustrates coupling of SDN and traditional networking – Hybrid SDN
  • Explores services, technologies, algorithms, and methods for data analysis in CSDN

The book is aimed at researchers and graduate students in software engineering, network security, computer networks, high performance computing, communications engineering, and intelligent systems.

This book consolidates the research relating to the security in SDN, CSDN, and Hybrid SDNs. The security enhancements derived from use of various SDN frameworks and the security challenges thus introduced, are also discussed. Overall, this book explains different architectures of SDNs and the security challenges needs for implementing them.

Software-Defined Networks (SDN) work by virtualization of the network and the Cognitive Software-Defined Network (CSDN) combines the efficiencies of SDN with cognitive learning algorithms and enhanced protocols to automatize SDN. Partial deployment of SDN along with traditional networking devices forms a Hybrid Software-Defined Network (HSDN). Software-Defined Network Frameworks: Security Issues and Use Cases consolidates the research relating to the security in SDN, CSDN, and Hybrid SDNs. The security enhancements derived from the use of various SDN frameworks and the security challenges thus introduced, are also discussed. Overall, this book explains the different architectures of SDNs and the security challenges needed for implementing them.

Features:

  • Illustrates different frameworks of SDN and their security issues in a single volume
  • Discusses design and assessment of efficient SDN northbound/southbound interfaces
  • Describes cognitive computing, affective computing, machine learning, and other novel tools
  • Illustrates coupling of SDN and traditional networking – Hybrid SDN
  • Explores services, technologies, algorithms, and methods for data analysis in CSDN

The book is aimed at researchers and graduate students in software engineering, network security, computer networks, high performance computing, communications engineering, and intelligent systems.

This book consolidates the research relating to the security in SDN, CSDN, and Hybrid SDNs. The security enhancements derived from use of various SDN frameworks and the security challenges thus introduced, are also discussed. Overall, this book explains different architectures of SDNs and the security challenges needs for implementing them.

Software-Defined Networks (SDN) work by virtualization of the network and the Cognitive Software-Defined Network (CSDN) combines the efficiencies of SDN with cognitive learning algorithms and enhanced protocols to automatize SDN. Partial deployment of SDN along with traditional networking devices forms a Hybrid Software-Defined Network (HSDN). Software-Defined Network Frameworks: Security Issues and Use Cases consolidates the research relating to the security in SDN, CSDN, and Hybrid SDNs. The security enhancements derived from the use of various SDN frameworks and the security challenges thus introduced, are also discussed. Overall, this book explains the different architectures of SDNs and the security challenges needed for implementing them.

Features:

  • Illustrates different frameworks of SDN and their security issues in a single volume
  • Discusses design and assessment of efficient SDN northbound/southbound interfaces
  • Describes cognitive computing, affective computing, machine learning, and other novel tools
  • Illustrates coupling of SDN and traditional networking – Hybrid SDN
  • Explores services, technologies, algorithms, and methods for data analysis in CSDN

The book is aimed at researchers and graduate students in software engineering, network security, computer networks, high performance computing, communications engineering, and intelligent systems.

This book consolidates the research relating to the security in SDN, CSDN, and Hybrid SDNs. The security enhancements derived from use of various SDN frameworks and the security challenges thus introduced, are also discussed. Overall, this book explains different architectures of SDNs and the security challenges needs for implementing them.

Software-Defined Networks (SDN) work by virtualization of the network and the Cognitive Software-Defined Network (CSDN) combines the efficiencies of SDN with cognitive learning algorithms and enhanced protocols to automatize SDN. Partial deployment of SDN along with traditional networking devices forms a Hybrid Software-Defined Network (HSDN). Software-Defined Network Frameworks: Security Issues and Use Cases consolidates the research relating to the security in SDN, CSDN, and Hybrid SDNs. The security enhancements derived from the use of various SDN frameworks and the security challenges thus introduced, are also discussed. Overall, this book explains the different architectures of SDNs and the security challenges needed for implementing them.

Features:

  • Illustrates different frameworks of SDN and their security issues in a single volume
  • Discusses design and assessment of efficient SDN northbound/southbound interfaces
  • Describes cognitive computing, affective computing, machine learning, and other novel tools
  • Illustrates coupling of SDN and traditional networking – Hybrid SDN
  • Explores services, technologies, algorithms, and methods for data analysis in CSDN

The book is aimed at researchers and graduate students in software engineering, network security, computer networks, high performance computing, communications engineering, and intelligent systems.

This book consolidates the research relating to the security in SDN, CSDN, and Hybrid SDNs. The security enhancements derived from use of various SDN frameworks and the security challenges thus introduced, are also discussed. Overall, this book explains different architectures of SDNs and the security challenges needs for implementing them.

Software-Defined Networks (SDN) work by virtualization of the network and the Cognitive Software-Defined Network (CSDN) combines the efficiencies of SDN with cognitive learning algorithms and enhanced protocols to automatize SDN. Partial deployment of SDN along with traditional networking devices forms a Hybrid Software-Defined Network (HSDN). Software-Defined Network Frameworks: Security Issues and Use Cases consolidates the research relating to the security in SDN, CSDN, and Hybrid SDNs. The security enhancements derived from the use of various SDN frameworks and the security challenges thus introduced, are also discussed. Overall, this book explains the different architectures of SDNs and the security challenges needed for implementing them.

Features:

  • Illustrates different frameworks of SDN and their security issues in a single volume
  • Discusses design and assessment of efficient SDN northbound/southbound interfaces
  • Describes cognitive computing, affective computing, machine learning, and other novel tools
  • Illustrates coupling of SDN and traditional networking – Hybrid SDN
  • Explores services, technologies, algorithms, and methods for data analysis in CSDN

The book is aimed at researchers and graduate students in software engineering, network security, computer networks, high performance computing, communications engineering, and intelligent systems.

This book consolidates the research relating to the security in SDN, CSDN, and Hybrid SDNs. The security enhancements derived from use of various SDN frameworks and the security challenges thus introduced, are also discussed. Overall, this book explains different architectures of SDNs and the security challenges needs for implementing them.

Software-Defined Networks (SDN) work by virtualization of the network and the Cognitive Software-Defined Network (CSDN) combines the efficiencies of SDN with cognitive learning algorithms and enhanced protocols to automatize SDN. Partial deployment of SDN along with traditional networking devices forms a Hybrid Software-Defined Network (HSDN). Software-Defined Network Frameworks: Security Issues and Use Cases consolidates the research relating to the security in SDN, CSDN, and Hybrid SDNs. The security enhancements derived from the use of various SDN frameworks and the security challenges thus introduced, are also discussed. Overall, this book explains the different architectures of SDNs and the security challenges needed for implementing them.

Features:

  • Illustrates different frameworks of SDN and their security issues in a single volume
  • Discusses design and assessment of efficient SDN northbound/southbound interfaces
  • Describes cognitive computing, affective computing, machine learning, and other novel tools
  • Illustrates coupling of SDN and traditional networking – Hybrid SDN
  • Explores services, technologies, algorithms, and methods for data analysis in CSDN

The book is aimed at researchers and graduate students in software engineering, network security, computer networks, high performance computing, communications engineering, and intelligent systems.

This book consolidates the research relating to the security in SDN, CSDN, and Hybrid SDNs. The security enhancements derived from use of various SDN frameworks and the security challenges thus introduced, are also discussed. Overall, this book explains different architectures of SDNs and the security challenges needs for implementing them.

Software-Defined Networks (SDN) work by virtualization of the network and the Cognitive Software-Defined Network (CSDN) combines the efficiencies of SDN with cognitive learning algorithms and enhanced protocols to automatize SDN. Partial deployment of SDN along with traditional networking devices forms a Hybrid Software-Defined Network (HSDN). Software-Defined Network Frameworks: Security Issues and Use Cases consolidates the research relating to the security in SDN, CSDN, and Hybrid SDNs. The security enhancements derived from the use of various SDN frameworks and the security challenges thus introduced, are also discussed. Overall, this book explains the different architectures of SDNs and the security challenges needed for implementing them.

Features:

  • Illustrates different frameworks of SDN and their security issues in a single volume
  • Discusses design and assessment of efficient SDN northbound/southbound interfaces
  • Describes cognitive computing, affective computing, machine learning, and other novel tools
  • Illustrates coupling of SDN and traditional networking – Hybrid SDN
  • Explores services, technologies, algorithms, and methods for data analysis in CSDN

The book is aimed at researchers and graduate students in software engineering, network security, computer networks, high performance computing, communications engineering, and intelligent systems.

This book consolidates the research relating to the security in SDN, CSDN, and Hybrid SDNs. The security enhancements derived from use of various SDN frameworks and the security challenges thus introduced, are also discussed. Overall, this book explains different architectures of SDNs and the security challenges needs for implementing them.

Software-Defined Networks (SDN) work by virtualization of the network and the Cognitive Software-Defined Network (CSDN) combines the efficiencies of SDN with cognitive learning algorithms and enhanced protocols to automatize SDN. Partial deployment of SDN along with traditional networking devices forms a Hybrid Software-Defined Network (HSDN). Software-Defined Network Frameworks: Security Issues and Use Cases consolidates the research relating to the security in SDN, CSDN, and Hybrid SDNs. The security enhancements derived from the use of various SDN frameworks and the security challenges thus introduced, are also discussed. Overall, this book explains the different architectures of SDNs and the security challenges needed for implementing them.

Features:

  • Illustrates different frameworks of SDN and their security issues in a single volume
  • Discusses design and assessment of efficient SDN northbound/southbound interfaces
  • Describes cognitive computing, affective computing, machine learning, and other novel tools
  • Illustrates coupling of SDN and traditional networking – Hybrid SDN
  • Explores services, technologies, algorithms, and methods for data analysis in CSDN

The book is aimed at researchers and graduate students in software engineering, network security, computer networks, high performance computing, communications engineering, and intelligent systems.

This book consolidates the research relating to the security in SDN, CSDN, and Hybrid SDNs. The security enhancements derived from use of various SDN frameworks and the security challenges thus introduced, are also discussed. Overall, this book explains different architectures of SDNs and the security challenges needs for implementing them.

Software-Defined Networks (SDN) work by virtualization of the network and the Cognitive Software-Defined Network (CSDN) combines the efficiencies of SDN with cognitive learning algorithms and enhanced protocols to automatize SDN. Partial deployment of SDN along with traditional networking devices forms a Hybrid Software-Defined Network (HSDN). Software-Defined Network Frameworks: Security Issues and Use Cases consolidates the research relating to the security in SDN, CSDN, and Hybrid SDNs. The security enhancements derived from the use of various SDN frameworks and the security challenges thus introduced, are also discussed. Overall, this book explains the different architectures of SDNs and the security challenges needed for implementing them.

Features:

  • Illustrates different frameworks of SDN and their security issues in a single volume
  • Discusses design and assessment of efficient SDN northbound/southbound interfaces
  • Describes cognitive computing, affective computing, machine learning, and other novel tools
  • Illustrates coupling of SDN and traditional networking – Hybrid SDN
  • Explores services, technologies, algorithms, and methods for data analysis in CSDN

The book is aimed at researchers and graduate students in software engineering, network security, computer networks, high performance computing, communications engineering, and intelligent systems.

This book consolidates the research relating to the security in SDN, CSDN, and Hybrid SDNs. The security enhancements derived from use of various SDN frameworks and the security challenges thus introduced, are also discussed. Overall, this book explains different architectures of SDNs and the security challenges needs for implementing them.

Software-Defined Networks (SDN) work by virtualization of the network and the Cognitive Software-Defined Network (CSDN) combines the efficiencies of SDN with cognitive learning algorithms and enhanced protocols to automatize SDN. Partial deployment of SDN along with traditional networking devices forms a Hybrid Software-Defined Network (HSDN). Software-Defined Network Frameworks: Security Issues and Use Cases consolidates the research relating to the security in SDN, CSDN, and Hybrid SDNs. The security enhancements derived from the use of various SDN frameworks and the security challenges thus introduced, are also discussed. Overall, this book explains the different architectures of SDNs and the security challenges needed for implementing them.

Features:

  • Illustrates different frameworks of SDN and their security issues in a single volume
  • Discusses design and assessment of efficient SDN northbound/southbound interfaces
  • Describes cognitive computing, affective computing, machine learning, and other novel tools
  • Illustrates coupling of SDN and traditional networking – Hybrid SDN
  • Explores services, technologies, algorithms, and methods for data analysis in CSDN

The book is aimed at researchers and graduate students in software engineering, network security, computer networks, high performance computing, communications engineering, and intelligent systems.

This book consolidates the research relating to the security in SDN, CSDN, and Hybrid SDNs. The security enhancements derived from use of various SDN frameworks and the security challenges thus introduced, are also discussed. Overall, this book explains different architectures of SDNs and the security challenges needs for implementing them.

Software-Defined Networks (SDN) work by virtualization of the network and the Cognitive Software-Defined Network (CSDN) combines the efficiencies of SDN with cognitive learning algorithms and enhanced protocols to automatize SDN. Partial deployment of SDN along with traditional networking devices forms a Hybrid Software-Defined Network (HSDN). Software-Defined Network Frameworks: Security Issues and Use Cases consolidates the research relating to the security in SDN, CSDN, and Hybrid SDNs. The security enhancements derived from the use of various SDN frameworks and the security challenges thus introduced, are also discussed. Overall, this book explains the different architectures of SDNs and the security challenges needed for implementing them.

Features:

  • Illustrates different frameworks of SDN and their security issues in a single volume
  • Discusses design and assessment of efficient SDN northbound/southbound interfaces
  • Describes cognitive computing, affective computing, machine learning, and other novel tools
  • Illustrates coupling of SDN and traditional networking – Hybrid SDN
  • Explores services, technologies, algorithms, and methods for data analysis in CSDN

The book is aimed at researchers and graduate students in software engineering, network security, computer networks, high performance computing, communications engineering, and intelligent systems.

This book consolidates the research relating to the security in SDN, CSDN, and Hybrid SDNs. The security enhancements derived from use of various SDN frameworks and the security challenges thus introduced, are also discussed. Overall, this book explains different architectures of SDNs and the security challenges needs for implementing them.

Software-Defined Networks (SDN) work by virtualization of the network and the Cognitive Software-Defined Network (CSDN) combines the efficiencies of SDN with cognitive learning algorithms and enhanced protocols to automatize SDN. Partial deployment of SDN along with traditional networking devices forms a Hybrid Software-Defined Network (HSDN). Software-Defined Network Frameworks: Security Issues and Use Cases consolidates the research relating to the security in SDN, CSDN, and Hybrid SDNs. The security enhancements derived from the use of various SDN frameworks and the security challenges thus introduced, are also discussed. Overall, this book explains the different architectures of SDNs and the security challenges needed for implementing them.

Features:

  • Illustrates different frameworks of SDN and their security issues in a single volume
  • Discusses design and assessment of efficient SDN northbound/southbound interfaces
  • Describes cognitive computing, affective computing, machine learning, and other novel tools
  • Illustrates coupling of SDN and traditional networking – Hybrid SDN
  • Explores services, technologies, algorithms, and methods for data analysis in CSDN

The book is aimed at researchers and graduate students in software engineering, network security, computer networks, high performance computing, communications engineering, and intelligent systems.

This book consolidates the research relating to the security in SDN, CSDN, and Hybrid SDNs. The security enhancements derived from use of various SDN frameworks and the security challenges thus introduced, are also discussed. Overall, this book explains different architectures of SDNs and the security challenges needs for implementing them.

Software-Defined Networks (SDN) work by virtualization of the network and the Cognitive Software-Defined Network (CSDN) combines the efficiencies of SDN with cognitive learning algorithms and enhanced protocols to automatize SDN. Partial deployment of SDN along with traditional networking devices forms a Hybrid Software-Defined Network (HSDN). Software-Defined Network Frameworks: Security Issues and Use Cases consolidates the research relating to the security in SDN, CSDN, and Hybrid SDNs. The security enhancements derived from the use of various SDN frameworks and the security challenges thus introduced, are also discussed. Overall, this book explains the different architectures of SDNs and the security challenges needed for implementing them.

Features:

  • Illustrates different frameworks of SDN and their security issues in a single volume
  • Discusses design and assessment of efficient SDN northbound/southbound interfaces
  • Describes cognitive computing, affective computing, machine learning, and other novel tools
  • Illustrates coupling of SDN and traditional networking – Hybrid SDN
  • Explores services, technologies, algorithms, and methods for data analysis in CSDN

The book is aimed at researchers and graduate students in software engineering, network security, computer networks, high performance computing, communications engineering, and intelligent systems.

This book consolidates the research relating to the security in SDN, CSDN, and Hybrid SDNs. The security enhancements derived from use of various SDN frameworks and the security challenges thus introduced, are also discussed. Overall, this book explains different architectures of SDNs and the security challenges needs for implementing them.

Software-Defined Networks (SDN) work by virtualization of the network and the Cognitive Software-Defined Network (CSDN) combines the efficiencies of SDN with cognitive learning algorithms and enhanced protocols to automatize SDN. Partial deployment of SDN along with traditional networking devices forms a Hybrid Software-Defined Network (HSDN). Software-Defined Network Frameworks: Security Issues and Use Cases consolidates the research relating to the security in SDN, CSDN, and Hybrid SDNs. The security enhancements derived from the use of various SDN frameworks and the security challenges thus introduced, are also discussed. Overall, this book explains the different architectures of SDNs and the security challenges needed for implementing them.

Features:

  • Illustrates different frameworks of SDN and their security issues in a single volume
  • Discusses design and assessment of efficient SDN northbound/southbound interfaces
  • Describes cognitive computing, affective computing, machine learning, and other novel tools
  • Illustrates coupling of SDN and traditional networking – Hybrid SDN
  • Explores services, technologies, algorithms, and methods for data analysis in CSDN

The book is aimed at researchers and graduate students in software engineering, network security, computer networks, high performance computing, communications engineering, and intelligent systems.

This book consolidates the research relating to the security in SDN, CSDN, and Hybrid SDNs. The security enhancements derived from use of various SDN frameworks and the security challenges thus introduced, are also discussed. Overall, this book explains different architectures of SDNs and the security challenges needs for implementing them.

Software-Defined Networks (SDN) work by virtualization of the network and the Cognitive Software-Defined Network (CSDN) combines the efficiencies of SDN with cognitive learning algorithms and enhanced protocols to automatize SDN. Partial deployment of SDN along with traditional networking devices forms a Hybrid Software-Defined Network (HSDN). Software-Defined Network Frameworks: Security Issues and Use Cases consolidates the research relating to the security in SDN, CSDN, and Hybrid SDNs. The security enhancements derived from the use of various SDN frameworks and the security challenges thus introduced, are also discussed. Overall, this book explains the different architectures of SDNs and the security challenges needed for implementing them.

Features:

  • Illustrates different frameworks of SDN and their security issues in a single volume
  • Discusses design and assessment of efficient SDN northbound/southbound interfaces
  • Describes cognitive computing, affective computing, machine learning, and other novel tools
  • Illustrates coupling of SDN and traditional networking – Hybrid SDN
  • Explores services, technologies, algorithms, and methods for data analysis in CSDN

The book is aimed at researchers and graduate students in software engineering, network security, computer networks, high performance computing, communications engineering, and intelligent systems.

This book consolidates the research relating to the security in SDN, CSDN, and Hybrid SDNs. The security enhancements derived from use of various SDN frameworks and the security challenges thus introduced, are also discussed. Overall, this book explains different architectures of SDNs and the security challenges needs for implementing them.

Software-Defined Networks (SDN) work by virtualization of the network and the Cognitive Software-Defined Network (CSDN) combines the efficiencies of SDN with cognitive learning algorithms and enhanced protocols to automatize SDN. Partial deployment of SDN along with traditional networking devices forms a Hybrid Software-Defined Network (HSDN). Software-Defined Network Frameworks: Security Issues and Use Cases consolidates the research relating to the security in SDN, CSDN, and Hybrid SDNs. The security enhancements derived from the use of various SDN frameworks and the security challenges thus introduced, are also discussed. Overall, this book explains the different architectures of SDNs and the security challenges needed for implementing them.

Features:

  • Illustrates different frameworks of SDN and their security issues in a single volume
  • Discusses design and assessment of efficient SDN northbound/southbound interfaces
  • Describes cognitive computing, affective computing, machine learning, and other novel tools
  • Illustrates coupling of SDN and traditional networking – Hybrid SDN
  • Explores services, technologies, algorithms, and methods for data analysis in CSDN

The book is aimed at researchers and graduate students in software engineering, network security, computer networks, high performance computing, communications engineering, and intelligent systems.

This book consolidates the research relating to the security in SDN, CSDN, and Hybrid SDNs. The security enhancements derived from use of various SDN frameworks and the security challenges thus introduced, are also discussed. Overall, this book explains different architectures of SDNs and the security challenges needs for implementing them.

Software-Defined Networks (SDN) work by virtualization of the network and the Cognitive Software-Defined Network (CSDN) combines the efficiencies of SDN with cognitive learning algorithms and enhanced protocols to automatize SDN. Partial deployment of SDN along with traditional networking devices forms a Hybrid Software-Defined Network (HSDN). Software-Defined Network Frameworks: Security Issues and Use Cases consolidates the research relating to the security in SDN, CSDN, and Hybrid SDNs. The security enhancements derived from the use of various SDN frameworks and the security challenges thus introduced, are also discussed. Overall, this book explains the different architectures of SDNs and the security challenges needed for implementing them.

Features:

  • Illustrates different frameworks of SDN and their security issues in a single volume
  • Discusses design and assessment of efficient SDN northbound/southbound interfaces
  • Describes cognitive computing, affective computing, machine learning, and other novel tools
  • Illustrates coupling of SDN and traditional networking – Hybrid SDN
  • Explores services, technologies, algorithms, and methods for data analysis in CSDN

The book is aimed at researchers and graduate students in software engineering, network security, computer networks, high performance computing, communications engineering, and intelligent systems.

This book consolidates the research relating to the security in SDN, CSDN, and Hybrid SDNs. The security enhancements derived from use of various SDN frameworks and the security challenges thus introduced, are also discussed. Overall, this book explains different architectures of SDNs and the security challenges needs for implementing them.

Software-Defined Networks (SDN) work by virtualization of the network and the Cognitive Software-Defined Network (CSDN) combines the efficiencies of SDN with cognitive learning algorithms and enhanced protocols to automatize SDN. Partial deployment of SDN along with traditional networking devices forms a Hybrid Software-Defined Network (HSDN). Software-Defined Network Frameworks: Security Issues and Use Cases consolidates the research relating to the security in SDN, CSDN, and Hybrid SDNs. The security enhancements derived from the use of various SDN frameworks and the security challenges thus introduced, are also discussed. Overall, this book explains the different architectures of SDNs and the security challenges needed for implementing them.

Features:

  • Illustrates different frameworks of SDN and their security issues in a single volume
  • Discusses design and assessment of efficient SDN northbound/southbound interfaces
  • Describes cognitive computing, affective computing, machine learning, and other novel tools
  • Illustrates coupling of SDN and traditional networking – Hybrid SDN
  • Explores services, technologies, algorithms, and methods for data analysis in CSDN

The book is aimed at researchers and graduate students in software engineering, network security, computer networks, high performance computing, communications engineering, and intelligent systems.

This book consolidates the research relating to the security in SDN, CSDN, and Hybrid SDNs. The security enhancements derived from use of various SDN frameworks and the security challenges thus introduced, are also discussed. Overall, this book explains different architectures of SDNs and the security challenges needs for implementing them.

Software-Defined Networks (SDN) work by virtualization of the network and the Cognitive Software-Defined Network (CSDN) combines the efficiencies of SDN with cognitive learning algorithms and enhanced protocols to automatize SDN. Partial deployment of SDN along with traditional networking devices forms a Hybrid Software-Defined Network (HSDN). Software-Defined Network Frameworks: Security Issues and Use Cases consolidates the research relating to the security in SDN, CSDN, and Hybrid SDNs. The security enhancements derived from the use of various SDN frameworks and the security challenges thus introduced, are also discussed. Overall, this book explains the different architectures of SDNs and the security challenges needed for implementing them.

Features:

  • Illustrates different frameworks of SDN and their security issues in a single volume
  • Discusses design and assessment of efficient SDN northbound/southbound interfaces
  • Describes cognitive computing, affective computing, machine learning, and other novel tools
  • Illustrates coupling of SDN and traditional networking – Hybrid SDN
  • Explores services, technologies, algorithms, and methods for data analysis in CSDN

The book is aimed at researchers and graduate students in software engineering, network security, computer networks, high performance computing, communications engineering, and intelligent systems.

This book consolidates the research relating to the security in SDN, CSDN, and Hybrid SDNs. The security enhancements derived from use of various SDN frameworks and the security challenges thus introduced, are also discussed. Overall, this book explains different architectures of SDNs and the security challenges needs for implementing them.

Software-Defined Networks (SDN) work by virtualization of the network and the Cognitive Software-Defined Network (CSDN) combines the efficiencies of SDN with cognitive learning algorithms and enhanced protocols to automatize SDN. Partial deployment of SDN along with traditional networking devices forms a Hybrid Software-Defined Network (HSDN). Software-Defined Network Frameworks: Security Issues and Use Cases consolidates the research relating to the security in SDN, CSDN, and Hybrid SDNs. The security enhancements derived from the use of various SDN frameworks and the security challenges thus introduced, are also discussed. Overall, this book explains the different architectures of SDNs and the security challenges needed for implementing them.

Features:

  • Illustrates different frameworks of SDN and their security issues in a single volume
  • Discusses design and assessment of efficient SDN northbound/southbound interfaces
  • Describes cognitive computing, affective computing, machine learning, and other novel tools
  • Illustrates coupling of SDN and traditional networking – Hybrid SDN
  • Explores services, technologies, algorithms, and methods for data analysis in CSDN

The book is aimed at researchers and graduate students in software engineering, network security, computer networks, high performance computing, communications engineering, and intelligent systems.

This book consolidates the research relating to the security in SDN, CSDN, and Hybrid SDNs. The security enhancements derived from use of various SDN frameworks and the security challenges thus introduced, are also discussed. Overall, this book explains different architectures of SDNs and the security challenges needs for implementing them.

Software-Defined Networks (SDN) work by virtualization of the network and the Cognitive Software-Defined Network (CSDN) combines the efficiencies of SDN with cognitive learning algorithms and enhanced protocols to automatize SDN. Partial deployment of SDN along with traditional networking devices forms a Hybrid Software-Defined Network (HSDN). Software-Defined Network Frameworks: Security Issues and Use Cases consolidates the research relating to the security in SDN, CSDN, and Hybrid SDNs. The security enhancements derived from the use of various SDN frameworks and the security challenges thus introduced, are also discussed. Overall, this book explains the different architectures of SDNs and the security challenges needed for implementing them.

Features:

  • Illustrates different frameworks of SDN and their security issues in a single volume
  • Discusses design and assessment of efficient SDN northbound/southbound interfaces
  • Describes cognitive computing, affective computing, machine learning, and other novel tools
  • Illustrates coupling of SDN and traditional networking – Hybrid SDN
  • Explores services, technologies, algorithms, and methods for data analysis in CSDN

The book is aimed at researchers and graduate students in software engineering, network security, computer networks, high performance computing, communications engineering, and intelligent systems.

This book consolidates the research relating to the security in SDN, CSDN, and Hybrid SDNs. The security enhancements derived from use of various SDN frameworks and the security challenges thus introduced, are also discussed. Overall, this book explains different architectures of SDNs and the security challenges needs for implementing them.

Software-Defined Networks (SDN) work by virtualization of the network and the Cognitive Software-Defined Network (CSDN) combines the efficiencies of SDN with cognitive learning algorithms and enhanced protocols to automatize SDN. Partial deployment of SDN along with traditional networking devices forms a Hybrid Software-Defined Network (HSDN). Software-Defined Network Frameworks: Security Issues and Use Cases consolidates the research relating to the security in SDN, CSDN, and Hybrid SDNs. The security enhancements derived from the use of various SDN frameworks and the security challenges thus introduced, are also discussed. Overall, this book explains the different architectures of SDNs and the security challenges needed for implementing them.

Features:

  • Illustrates different frameworks of SDN and their security issues in a single volume
  • Discusses design and assessment of efficient SDN northbound/southbound interfaces
  • Describes cognitive computing, affective computing, machine learning, and other novel tools
  • Illustrates coupling of SDN and traditional networking – Hybrid SDN
  • Explores services, technologies, algorithms, and methods for data analysis in CSDN

The book is aimed at researchers and graduate students in software engineering, network security, computer networks, high performance computing, communications engineering, and intelligent systems.

This book consolidates the research relating to the security in SDN, CSDN, and Hybrid SDNs. The security enhancements derived from use of various SDN frameworks and the security challenges thus introduced, are also discussed. Overall, this book explains different architectures of SDNs and the security challenges needs for implementing them.

Software-Defined Networks (SDN) work by virtualization of the network and the Cognitive Software-Defined Network (CSDN) combines the efficiencies of SDN with cognitive learning algorithms and enhanced protocols to automatize SDN. Partial deployment of SDN along with traditional networking devices forms a Hybrid Software-Defined Network (HSDN). Software-Defined Network Frameworks: Security Issues and Use Cases consolidates the research relating to the security in SDN, CSDN, and Hybrid SDNs. The security enhancements derived from the use of various SDN frameworks and the security challenges thus introduced, are also discussed. Overall, this book explains the different architectures of SDNs and the security challenges needed for implementing them.

Features:

  • Illustrates different frameworks of SDN and their security issues in a single volume
  • Discusses design and assessment of efficient SDN northbound/southbound interfaces
  • Describes cognitive computing, affective computing, machine learning, and other novel tools
  • Illustrates coupling of SDN and traditional networking – Hybrid SDN
  • Explores services, technologies, algorithms, and methods for data analysis in CSDN

The book is aimed at researchers and graduate students in software engineering, network security, computer networks, high performance computing, communications engineering, and intelligent systems.

This book consolidates the research relating to the security in SDN, CSDN, and Hybrid SDNs. The security enhancements derived from use of various SDN frameworks and the security challenges thus introduced, are also discussed. Overall, this book explains different architectures of SDNs and the security challenges needs for implementing them.

Software-Defined Networks (SDN) work by virtualization of the network and the Cognitive Software-Defined Network (CSDN) combines the efficiencies of SDN with cognitive learning algorithms and enhanced protocols to automatize SDN. Partial deployment of SDN along with traditional networking devices forms a Hybrid Software-Defined Network (HSDN). Software-Defined Network Frameworks: Security Issues and Use Cases consolidates the research relating to the security in SDN, CSDN, and Hybrid SDNs. The security enhancements derived from the use of various SDN frameworks and the security challenges thus introduced, are also discussed. Overall, this book explains the different architectures of SDNs and the security challenges needed for implementing them.

Features:

  • Illustrates different frameworks of SDN and their security issues in a single volume
  • Discusses design and assessment of efficient SDN northbound/southbound interfaces
  • Describes cognitive computing, affective computing, machine learning, and other novel tools
  • Illustrates coupling of SDN and traditional networking – Hybrid SDN
  • Explores services, technologies, algorithms, and methods for data analysis in CSDN

The book is aimed at researchers and graduate students in software engineering, network security, computer networks, high performance computing, communications engineering, and intelligent systems.

This book consolidates the research relating to the security in SDN, CSDN, and Hybrid SDNs. The security enhancements derived from use of various SDN frameworks and the security challenges thus introduced, are also discussed. Overall, this book explains different architectures of SDNs and the security challenges needs for implementing them.

Software-Defined Networks (SDN) work by virtualization of the network and the Cognitive Software-Defined Network (CSDN) combines the efficiencies of SDN with cognitive learning algorithms and enhanced protocols to automatize SDN. Partial deployment of SDN along with traditional networking devices forms a Hybrid Software-Defined Network (HSDN). Software-Defined Network Frameworks: Security Issues and Use Cases consolidates the research relating to the security in SDN, CSDN, and Hybrid SDNs. The security enhancements derived from the use of various SDN frameworks and the security challenges thus introduced, are also discussed. Overall, this book explains the different architectures of SDNs and the security challenges needed for implementing them.

Features:

  • Illustrates different frameworks of SDN and their security issues in a single volume
  • Discusses design and assessment of efficient SDN northbound/southbound interfaces
  • Describes cognitive computing, affective computing, machine learning, and other novel tools
  • Illustrates coupling of SDN and traditional networking – Hybrid SDN
  • Explores services, technologies, algorithms, and methods for data analysis in CSDN

The book is aimed at researchers and graduate students in software engineering, network security, computer networks, high performance computing, communications engineering, and intelligent systems.

This book consolidates the research relating to the security in SDN, CSDN, and Hybrid SDNs. The security enhancements derived from use of various SDN frameworks and the security challenges thus introduced, are also discussed. Overall, this book explains different architectures of SDNs and the security challenges needs for implementing them.

Software-Defined Networks (SDN) work by virtualization of the network and the Cognitive Software-Defined Network (CSDN) combines the efficiencies of SDN with cognitive learning algorithms and enhanced protocols to automatize SDN. Partial deployment of SDN along with traditional networking devices forms a Hybrid Software-Defined Network (HSDN). Software-Defined Network Frameworks: Security Issues and Use Cases consolidates the research relating to the security in SDN, CSDN, and Hybrid SDNs. The security enhancements derived from the use of various SDN frameworks and the security challenges thus introduced, are also discussed. Overall, this book explains the different architectures of SDNs and the security challenges needed for implementing them.

Features:

  • Illustrates different frameworks of SDN and their security issues in a single volume
  • Discusses design and assessment of efficient SDN northbound/southbound interfaces
  • Describes cognitive computing, affective computing, machine learning, and other novel tools
  • Illustrates coupling of SDN and traditional networking – Hybrid SDN
  • Explores services, technologies, algorithms, and methods for data analysis in CSDN

The book is aimed at researchers and graduate students in software engineering, network security, computer networks, high performance computing, communications engineering, and intelligent systems.

This book consolidates the research relating to the security in SDN, CSDN, and Hybrid SDNs. The security enhancements derived from use of various SDN frameworks and the security challenges thus introduced, are also discussed. Overall, this book explains different architectures of SDNs and the security challenges needs for implementing them.

Software-Defined Networks (SDN) work by virtualization of the network and the Cognitive Software-Defined Network (CSDN) combines the efficiencies of SDN with cognitive learning algorithms and enhanced protocols to automatize SDN. Partial deployment of SDN along with traditional networking devices forms a Hybrid Software-Defined Network (HSDN). Software-Defined Network Frameworks: Security Issues and Use Cases consolidates the research relating to the security in SDN, CSDN, and Hybrid SDNs. The security enhancements derived from the use of various SDN frameworks and the security challenges thus introduced, are also discussed. Overall, this book explains the different architectures of SDNs and the security challenges needed for implementing them.

Features:

  • Illustrates different frameworks of SDN and their security issues in a single volume
  • Discusses design and assessment of efficient SDN northbound/southbound interfaces
  • Describes cognitive computing, affective computing, machine learning, and other novel tools
  • Illustrates coupling of SDN and traditional networking – Hybrid SDN
  • Explores services, technologies, algorithms, and methods for data analysis in CSDN

The book is aimed at researchers and graduate students in software engineering, network security, computer networks, high performance computing, communications engineering, and intelligent systems.

This book consolidates the research relating to the security in SDN, CSDN, and Hybrid SDNs. The security enhancements derived from use of various SDN frameworks and the security challenges thus introduced, are also discussed. Overall, this book explains different architectures of SDNs and the security challenges needs for implementing them.

Software-Defined Networks (SDN) work by virtualization of the network and the Cognitive Software-Defined Network (CSDN) combines the efficiencies of SDN with cognitive learning algorithms and enhanced protocols to automatize SDN. Partial deployment of SDN along with traditional networking devices forms a Hybrid Software-Defined Network (HSDN). Software-Defined Network Frameworks: Security Issues and Use Cases consolidates the research relating to the security in SDN, CSDN, and Hybrid SDNs. The security enhancements derived from the use of various SDN frameworks and the security challenges thus introduced, are also discussed. Overall, this book explains the different architectures of SDNs and the security challenges needed for implementing them.

Features:

  • Illustrates different frameworks of SDN and their security issues in a single volume
  • Discusses design and assessment of efficient SDN northbound/southbound interfaces
  • Describes cognitive computing, affective computing, machine learning, and other novel tools
  • Illustrates coupling of SDN and traditional networking – Hybrid SDN
  • Explores services, technologies, algorithms, and methods for data analysis in CSDN

The book is aimed at researchers and graduate students in software engineering, network security, computer networks, high performance computing, communications engineering, and intelligent systems.

This book consolidates the research relating to the security in SDN, CSDN, and Hybrid SDNs. The security enhancements derived from use of various SDN frameworks and the security challenges thus introduced, are also discussed. Overall, this book explains different architectures of SDNs and the security challenges needs for implementing them.

Software-Defined Networks (SDN) work by virtualization of the network and the Cognitive Software-Defined Network (CSDN) combines the efficiencies of SDN with cognitive learning algorithms and enhanced protocols to automatize SDN. Partial deployment of SDN along with traditional networking devices forms a Hybrid Software-Defined Network (HSDN). Software-Defined Network Frameworks: Security Issues and Use Cases consolidates the research relating to the security in SDN, CSDN, and Hybrid SDNs. The security enhancements derived from the use of various SDN frameworks and the security challenges thus introduced, are also discussed. Overall, this book explains the different architectures of SDNs and the security challenges needed for implementing them.

Features:

  • Illustrates different frameworks of SDN and their security issues in a single volume
  • Discusses design and assessment of efficient SDN northbound/southbound interfaces
  • Describes cognitive computing, affective computing, machine learning, and other novel tools
  • Illustrates coupling of SDN and traditional networking – Hybrid SDN
  • Explores services, technologies, algorithms, and methods for data analysis in CSDN

The book is aimed at researchers and graduate students in software engineering, network security, computer networks, high performance computing, communications engineering, and intelligent systems.

This book consolidates the research relating to the security in SDN, CSDN, and Hybrid SDNs. The security enhancements derived from use of various SDN frameworks and the security challenges thus introduced, are also discussed. Overall, this book explains different architectures of SDNs and the security challenges needs for implementing them.

Software-Defined Networks (SDN) work by virtualization of the network and the Cognitive Software-Defined Network (CSDN) combines the efficiencies of SDN with cognitive learning algorithms and enhanced protocols to automatize SDN. Partial deployment of SDN along with traditional networking devices forms a Hybrid Software-Defined Network (HSDN). Software-Defined Network Frameworks: Security Issues and Use Cases consolidates the research relating to the security in SDN, CSDN, and Hybrid SDNs. The security enhancements derived from the use of various SDN frameworks and the security challenges thus introduced, are also discussed. Overall, this book explains the different architectures of SDNs and the security challenges needed for implementing them.

Features:

  • Illustrates different frameworks of SDN and their security issues in a single volume
  • Discusses design and assessment of efficient SDN northbound/southbound interfaces
  • Describes cognitive computing, affective computing, machine learning, and other novel tools
  • Illustrates coupling of SDN and traditional networking – Hybrid SDN
  • Explores services, technologies, algorithms, and methods for data analysis in CSDN

The book is aimed at researchers and graduate students in software engineering, network security, computer networks, high performance computing, communications engineering, and intelligent systems.

This book consolidates the research relating to the security in SDN, CSDN, and Hybrid SDNs. The security enhancements derived from use of various SDN frameworks and the security challenges thus introduced, are also discussed. Overall, this book explains different architectures of SDNs and the security challenges needs for implementing them.

Software-Defined Networks (SDN) work by virtualization of the network and the Cognitive Software-Defined Network (CSDN) combines the efficiencies of SDN with cognitive learning algorithms and enhanced protocols to automatize SDN. Partial deployment of SDN along with traditional networking devices forms a Hybrid Software-Defined Network (HSDN). Software-Defined Network Frameworks: Security Issues and Use Cases consolidates the research relating to the security in SDN, CSDN, and Hybrid SDNs. The security enhancements derived from the use of various SDN frameworks and the security challenges thus introduced, are also discussed. Overall, this book explains the different architectures of SDNs and the security challenges needed for implementing them.

Features:

  • Illustrates different frameworks of SDN and their security issues in a single volume
  • Discusses design and assessment of efficient SDN northbound/southbound interfaces
  • Describes cognitive computing, affective computing, machine learning, and other novel tools
  • Illustrates coupling of SDN and traditional networking – Hybrid SDN
  • Explores services, technologies, algorithms, and methods for data analysis in CSDN

The book is aimed at researchers and graduate students in software engineering, network security, computer networks, high performance computing, communications engineering, and intelligent systems.

This book consolidates the research relating to the security in SDN, CSDN, and Hybrid SDNs. The security enhancements derived from use of various SDN frameworks and the security challenges thus introduced, are also discussed. Overall, this book explains different architectures of SDNs and the security challenges needs for implementing them.

Software-Defined Networks (SDN) work by virtualization of the network and the Cognitive Software-Defined Network (CSDN) combines the efficiencies of SDN with cognitive learning algorithms and enhanced protocols to automatize SDN. Partial deployment of SDN along with traditional networking devices forms a Hybrid Software-Defined Network (HSDN). Software-Defined Network Frameworks: Security Issues and Use Cases consolidates the research relating to the security in SDN, CSDN, and Hybrid SDNs. The security enhancements derived from the use of various SDN frameworks and the security challenges thus introduced, are also discussed. Overall, this book explains the different architectures of SDNs and the security challenges needed for implementing them.

Features:

  • Illustrates different frameworks of SDN and their security issues in a single volume
  • Discusses design and assessment of efficient SDN northbound/southbound interfaces
  • Describes cognitive computing, affective computing, machine learning, and other novel tools
  • Illustrates coupling of SDN and traditional networking – Hybrid SDN
  • Explores services, technologies, algorithms, and methods for data analysis in CSDN

The book is aimed at researchers and graduate students in software engineering, network security, computer networks, high performance computing, communications engineering, and intelligent systems.

This book consolidates the research relating to the security in SDN, CSDN, and Hybrid SDNs. The security enhancements derived from use of various SDN frameworks and the security challenges thus introduced, are also discussed. Overall, this book explains different architectures of SDNs and the security challenges needs for implementing them.

Software-Defined Networks (SDN) work by virtualization of the network and the Cognitive Software-Defined Network (CSDN) combines the efficiencies of SDN with cognitive learning algorithms and enhanced protocols to automatize SDN. Partial deployment of SDN along with traditional networking devices forms a Hybrid Software-Defined Network (HSDN). Software-Defined Network Frameworks: Security Issues and Use Cases consolidates the research relating to the security in SDN, CSDN, and Hybrid SDNs. The security enhancements derived from the use of various SDN frameworks and the security challenges thus introduced, are also discussed. Overall, this book explains the different architectures of SDNs and the security challenges needed for implementing them.

Features:

  • Illustrates different frameworks of SDN and their security issues in a single volume
  • Discusses design and assessment of efficient SDN northbound/southbound interfaces
  • Describes cognitive computing, affective computing, machine learning, and other novel tools
  • Illustrates coupling of SDN and traditional networking – Hybrid SDN
  • Explores services, technologies, algorithms, and methods for data analysis in CSDN

The book is aimed at researchers and graduate students in software engineering, network security, computer networks, high performance computing, communications engineering, and intelligent systems.

This book consolidates the research relating to the security in SDN, CSDN, and Hybrid SDNs. The security enhancements derived from use of various SDN frameworks and the security challenges thus introduced, are also discussed. Overall, this book explains different architectures of SDNs and the security challenges needs for implementing them.

Software-Defined Networks (SDN) work by virtualization of the network and the Cognitive Software-Defined Network (CSDN) combines the efficiencies of SDN with cognitive learning algorithms and enhanced protocols to automatize SDN. Partial deployment of SDN along with traditional networking devices forms a Hybrid Software-Defined Network (HSDN). Software-Defined Network Frameworks: Security Issues and Use Cases consolidates the research relating to the security in SDN, CSDN, and Hybrid SDNs. The security enhancements derived from the use of various SDN frameworks and the security challenges thus introduced, are also discussed. Overall, this book explains the different architectures of SDNs and the security challenges needed for implementing them.

Features:

  • Illustrates different frameworks of SDN and their security issues in a single volume
  • Discusses design and assessment of efficient SDN northbound/southbound interfaces
  • Describes cognitive computing, affective computing, machine learning, and other novel tools
  • Illustrates coupling of SDN and traditional networking – Hybrid SDN
  • Explores services, technologies, algorithms, and methods for data analysis in CSDN

The book is aimed at researchers and graduate students in software engineering, network security, computer networks, high performance computing, communications engineering, and intelligent systems.

This book consolidates the research relating to the security in SDN, CSDN, and Hybrid SDNs. The security enhancements derived from use of various SDN frameworks and the security challenges thus introduced, are also discussed. Overall, this book explains different architectures of SDNs and the security challenges needs for implementing them.

Software-Defined Networks (SDN) work by virtualization of the network and the Cognitive Software-Defined Network (CSDN) combines the efficiencies of SDN with cognitive learning algorithms and enhanced protocols to automatize SDN. Partial deployment of SDN along with traditional networking devices forms a Hybrid Software-Defined Network (HSDN). Software-Defined Network Frameworks: Security Issues and Use Cases consolidates the research relating to the security in SDN, CSDN, and Hybrid SDNs. The security enhancements derived from the use of various SDN frameworks and the security challenges thus introduced, are also discussed. Overall, this book explains the different architectures of SDNs and the security challenges needed for implementing them.

Features:

  • Illustrates different frameworks of SDN and their security issues in a single volume
  • Discusses design and assessment of efficient SDN northbound/southbound interfaces
  • Describes cognitive computing, affective computing, machine learning, and other novel tools
  • Illustrates coupling of SDN and traditional networking – Hybrid SDN
  • Explores services, technologies, algorithms, and methods for data analysis in CSDN

The book is aimed at researchers and graduate students in software engineering, network security, computer networks, high performance computing, communications engineering, and intelligent systems.

This book consolidates the research relating to the security in SDN, CSDN, and Hybrid SDNs. The security enhancements derived from use of various SDN frameworks and the security challenges thus introduced, are also discussed. Overall, this book explains different architectures of SDNs and the security challenges needs for implementing them.

Software-Defined Networks (SDN) work by virtualization of the network and the Cognitive Software-Defined Network (CSDN) combines the efficiencies of SDN with cognitive learning algorithms and enhanced protocols to automatize SDN. Partial deployment of SDN along with traditional networking devices forms a Hybrid Software-Defined Network (HSDN). Software-Defined Network Frameworks: Security Issues and Use Cases consolidates the research relating to the security in SDN, CSDN, and Hybrid SDNs. The security enhancements derived from the use of various SDN frameworks and the security challenges thus introduced, are also discussed. Overall, this book explains the different architectures of SDNs and the security challenges needed for implementing them.

Features:

  • Illustrates different frameworks of SDN and their security issues in a single volume
  • Discusses design and assessment of efficient SDN northbound/southbound interfaces
  • Describes cognitive computing, affective computing, machine learning, and other novel tools
  • Illustrates coupling of SDN and traditional networking – Hybrid SDN
  • Explores services, technologies, algorithms, and methods for data analysis in CSDN

The book is aimed at researchers and graduate students in software engineering, network security, computer networks, high performance computing, communications engineering, and intelligent systems.

This book consolidates the research relating to the security in SDN, CSDN, and Hybrid SDNs. The security enhancements derived from use of various SDN frameworks and the security challenges thus introduced, are also discussed. Overall, this book explains different architectures of SDNs and the security challenges needs for implementing them.

Software-Defined Networks (SDN) work by virtualization of the network and the Cognitive Software-Defined Network (CSDN) combines the efficiencies of SDN with cognitive learning algorithms and enhanced protocols to automatize SDN. Partial deployment of SDN along with traditional networking devices forms a Hybrid Software-Defined Network (HSDN). Software-Defined Network Frameworks: Security Issues and Use Cases consolidates the research relating to the security in SDN, CSDN, and Hybrid SDNs. The security enhancements derived from the use of various SDN frameworks and the security challenges thus introduced, are also discussed. Overall, this book explains the different architectures of SDNs and the security challenges needed for implementing them.

Features:

  • Illustrates different frameworks of SDN and their security issues in a single volume
  • Discusses design and assessment of efficient SDN northbound/southbound interfaces
  • Describes cognitive computing, affective computing, machine learning, and other novel tools
  • Illustrates coupling of SDN and traditional networking – Hybrid SDN
  • Explores services, technologies, algorithms, and methods for data analysis in CSDN

The book is aimed at researchers and graduate students in software engineering, network security, computer networks, high performance computing, communications engineering, and intelligent systems.

This book consolidates the research relating to the security in SDN, CSDN, and Hybrid SDNs. The security enhancements derived from use of various SDN frameworks and the security challenges thus introduced, are also discussed. Overall, this book explains different architectures of SDNs and the security challenges needs for implementing them.

Software-Defined Networks (SDN) work by virtualization of the network and the Cognitive Software-Defined Network (CSDN) combines the efficiencies of SDN with cognitive learning algorithms and enhanced protocols to automatize SDN. Partial deployment of SDN along with traditional networking devices forms a Hybrid Software-Defined Network (HSDN). Software-Defined Network Frameworks: Security Issues and Use Cases consolidates the research relating to the security in SDN, CSDN, and Hybrid SDNs. The security enhancements derived from the use of various SDN frameworks and the security challenges thus introduced, are also discussed. Overall, this book explains the different architectures of SDNs and the security challenges needed for implementing them.

Features:

  • Illustrates different frameworks of SDN and their security issues in a single volume
  • Discusses design and assessment of efficient SDN northbound/southbound interfaces
  • Describes cognitive computing, affective computing, machine learning, and other novel tools
  • Illustrates coupling of SDN and traditional networking – Hybrid SDN
  • Explores services, technologies, algorithms, and methods for data analysis in CSDN

The book is aimed at researchers and graduate students in software engineering, network security, computer networks, high performance computing, communications engineering, and intelligent systems.

This book consolidates the research relating to the security in SDN, CSDN, and Hybrid SDNs. The security enhancements derived from use of various SDN frameworks and the security challenges thus introduced, are also discussed. Overall, this book explains different architectures of SDNs and the security challenges needs for implementing them.

Software-Defined Networks (SDN) work by virtualization of the network and the Cognitive Software-Defined Network (CSDN) combines the efficiencies of SDN with cognitive learning algorithms and enhanced protocols to automatize SDN. Partial deployment of SDN along with traditional networking devices forms a Hybrid Software-Defined Network (HSDN). Software-Defined Network Frameworks: Security Issues and Use Cases consolidates the research relating to the security in SDN, CSDN, and Hybrid SDNs. The security enhancements derived from the use of various SDN frameworks and the security challenges thus introduced, are also discussed. Overall, this book explains the different architectures of SDNs and the security challenges needed for implementing them.

Features:

  • Illustrates different frameworks of SDN and their security issues in a single volume
  • Discusses design and assessment of efficient SDN northbound/southbound interfaces
  • Describes cognitive computing, affective computing, machine learning, and other novel tools
  • Illustrates coupling of SDN and traditional networking – Hybrid SDN
  • Explores services, technologies, algorithms, and methods for data analysis in CSDN

The book is aimed at researchers and graduate students in software engineering, network security, computer networks, high performance computing, communications engineering, and intelligent systems.

This book consolidates the research relating to the security in SDN, CSDN, and Hybrid SDNs. The security enhancements derived from use of various SDN frameworks and the security challenges thus introduced, are also discussed. Overall, this book explains different architectures of SDNs and the security challenges needs for implementing them.

Software-Defined Networks (SDN) work by virtualization of the network and the Cognitive Software-Defined Network (CSDN) combines the efficiencies of SDN with cognitive learning algorithms and enhanced protocols to automatize SDN. Partial deployment of SDN along with traditional networking devices forms a Hybrid Software-Defined Network (HSDN). Software-Defined Network Frameworks: Security Issues and Use Cases consolidates the research relating to the security in SDN, CSDN, and Hybrid SDNs. The security enhancements derived from the use of various SDN frameworks and the security challenges thus introduced, are also discussed. Overall, this book explains the different architectures of SDNs and the security challenges needed for implementing them.

Features:

  • Illustrates different frameworks of SDN and their security issues in a single volume
  • Discusses design and assessment of efficient SDN northbound/southbound interfaces
  • Describes cognitive computing, affective computing, machine learning, and other novel tools
  • Illustrates coupling of SDN and traditional networking – Hybrid SDN
  • Explores services, technologies, algorithms, and methods for data analysis in CSDN

The book is aimed at researchers and graduate students in software engineering, network security, computer networks, high performance computing, communications engineering, and intelligent systems.

This book consolidates the research relating to the security in SDN, CSDN, and Hybrid SDNs. The security enhancements derived from use of various SDN frameworks and the security challenges thus introduced, are also discussed. Overall, this book explains different architectures of SDNs and the security challenges needs for implementing them.

Software-Defined Networks (SDN) work by virtualization of the network and the Cognitive Software-Defined Network (CSDN) combines the efficiencies of SDN with cognitive learning algorithms and enhanced protocols to automatize SDN. Partial deployment of SDN along with traditional networking devices forms a Hybrid Software-Defined Network (HSDN). Software-Defined Network Frameworks: Security Issues and Use Cases consolidates the research relating to the security in SDN, CSDN, and Hybrid SDNs. The security enhancements derived from the use of various SDN frameworks and the security challenges thus introduced, are also discussed. Overall, this book explains the different architectures of SDNs and the security challenges needed for implementing them.

Features:

  • Illustrates different frameworks of SDN and their security issues in a single volume
  • Discusses design and assessment of efficient SDN northbound/southbound interfaces
  • Describes cognitive computing, affective computing, machine learning, and other novel tools
  • Illustrates coupling of SDN and traditional networking – Hybrid SDN
  • Explores services, technologies, algorithms, and methods for data analysis in CSDN

The book is aimed at researchers and graduate students in software engineering, network security, computer networks, high performance computing, communications engineering, and intelligent systems.

This book consolidates the research relating to the security in SDN, CSDN, and Hybrid SDNs. The security enhancements derived from use of various SDN frameworks and the security challenges thus introduced, are also discussed. Overall, this book explains different architectures of SDNs and the security challenges needs for implementing them.

Software-Defined Networks (SDN) work by virtualization of the network and the Cognitive Software-Defined Network (CSDN) combines the efficiencies of SDN with cognitive learning algorithms and enhanced protocols to automatize SDN. Partial deployment of SDN along with traditional networking devices forms a Hybrid Software-Defined Network (HSDN). Software-Defined Network Frameworks: Security Issues and Use Cases consolidates the research relating to the security in SDN, CSDN, and Hybrid SDNs. The security enhancements derived from the use of various SDN frameworks and the security challenges thus introduced, are also discussed. Overall, this book explains the different architectures of SDNs and the security challenges needed for implementing them.

Features:

  • Illustrates different frameworks of SDN and their security issues in a single volume
  • Discusses design and assessment of efficient SDN northbound/southbound interfaces
  • Describes cognitive computing, affective computing, machine learning, and other novel tools
  • Illustrates coupling of SDN and traditional networking – Hybrid SDN
  • Explores services, technologies, algorithms, and methods for data analysis in CSDN

The book is aimed at researchers and graduate students in software engineering, network security, computer networks, high performance computing, communications engineering, and intelligent systems.

This book consolidates the research relating to the security in SDN, CSDN, and Hybrid SDNs. The security enhancements derived from use of various SDN frameworks and the security challenges thus introduced, are also discussed. Overall, this book explains different architectures of SDNs and the security challenges needs for implementing them.

Software-Defined Networks (SDN) work by virtualization of the network and the Cognitive Software-Defined Network (CSDN) combines the efficiencies of SDN with cognitive learning algorithms and enhanced protocols to automatize SDN. Partial deployment of SDN along with traditional networking devices forms a Hybrid Software-Defined Network (HSDN). Software-Defined Network Frameworks: Security Issues and Use Cases consolidates the research relating to the security in SDN, CSDN, and Hybrid SDNs. The security enhancements derived from the use of various SDN frameworks and the security challenges thus introduced, are also discussed. Overall, this book explains the different architectures of SDNs and the security challenges needed for implementing them.

Features:

  • Illustrates different frameworks of SDN and their security issues in a single volume
  • Discusses design and assessment of efficient SDN northbound/southbound interfaces
  • Describes cognitive computing, affective computing, machine learning, and other novel tools
  • Illustrates coupling of SDN and traditional networking – Hybrid SDN
  • Explores services, technologies, algorithms, and methods for data analysis in CSDN

The book is aimed at researchers and graduate students in software engineering, network security, computer networks, high performance computing, communications engineering, and intelligent systems.

This book consolidates the research relating to the security in SDN, CSDN, and Hybrid SDNs. The security enhancements derived from use of various SDN frameworks and the security challenges thus introduced, are also discussed. Overall, this book explains different architectures of SDNs and the security challenges needs for implementing them.

Software-Defined Networks (SDN) work by virtualization of the network and the Cognitive Software-Defined Network (CSDN) combines the efficiencies of SDN with cognitive learning algorithms and enhanced protocols to automatize SDN. Partial deployment of SDN along with traditional networking devices forms a Hybrid Software-Defined Network (HSDN). Software-Defined Network Frameworks: Security Issues and Use Cases consolidates the research relating to the security in SDN, CSDN, and Hybrid SDNs. The security enhancements derived from the use of various SDN frameworks and the security challenges thus introduced, are also discussed. Overall, this book explains the different architectures of SDNs and the security challenges needed for implementing them.

Features:

  • Illustrates different frameworks of SDN and their security issues in a single volume
  • Discusses design and assessment of efficient SDN northbound/southbound interfaces
  • Describes cognitive computing, affective computing, machine learning, and other novel tools
  • Illustrates coupling of SDN and traditional networking – Hybrid SDN
  • Explores services, technologies, algorithms, and methods for data analysis in CSDN

The book is aimed at researchers and graduate students in software engineering, network security, computer networks, high performance computing, communications engineering, and intelligent systems.

This book consolidates the research relating to the security in SDN, CSDN, and Hybrid SDNs. The security enhancements derived from use of various SDN frameworks and the security challenges thus introduced, are also discussed. Overall, this book explains different architectures of SDNs and the security challenges needs for implementing them.

Software-Defined Networks (SDN) work by virtualization of the network and the Cognitive Software-Defined Network (CSDN) combines the efficiencies of SDN with cognitive learning algorithms and enhanced protocols to automatize SDN. Partial deployment of SDN along with traditional networking devices forms a Hybrid Software-Defined Network (HSDN). Software-Defined Network Frameworks: Security Issues and Use Cases consolidates the research relating to the security in SDN, CSDN, and Hybrid SDNs. The security enhancements derived from the use of various SDN frameworks and the security challenges thus introduced, are also discussed. Overall, this book explains the different architectures of SDNs and the security challenges needed for implementing them.

Features:

  • Illustrates different frameworks of SDN and their security issues in a single volume
  • Discusses design and assessment of efficient SDN northbound/southbound interfaces
  • Describes cognitive computing, affective computing, machine learning, and other novel tools
  • Illustrates coupling of SDN and traditional networking – Hybrid SDN
  • Explores services, technologies, algorithms, and methods for data analysis in CSDN

The book is aimed at researchers and graduate students in software engineering, network security, computer networks, high performance computing, communications engineering, and intelligent systems.

This book consolidates the research relating to the security in SDN, CSDN, and Hybrid SDNs. The security enhancements derived from use of various SDN frameworks and the security challenges thus introduced, are also discussed. Overall, this book explains different architectures of SDNs and the security challenges needs for implementing them.

Software-Defined Networks (SDN) work by virtualization of the network and the Cognitive Software-Defined Network (CSDN) combines the efficiencies of SDN with cognitive learning algorithms and enhanced protocols to automatize SDN. Partial deployment of SDN along with traditional networking devices forms a Hybrid Software-Defined Network (HSDN). Software-Defined Network Frameworks: Security Issues and Use Cases consolidates the research relating to the security in SDN, CSDN, and Hybrid SDNs. The security enhancements derived from the use of various SDN frameworks and the security challenges thus introduced, are also discussed. Overall, this book explains the different architectures of SDNs and the security challenges needed for implementing them.

Features:

  • Illustrates different frameworks of SDN and their security issues in a single volume
  • Discusses design and assessment of efficient SDN northbound/southbound interfaces
  • Describes cognitive computing, affective computing, machine learning, and other novel tools
  • Illustrates coupling of SDN and traditional networking – Hybrid SDN
  • Explores services, technologies, algorithms, and methods for data analysis in CSDN

The book is aimed at researchers and graduate students in software engineering, network security, computer networks, high performance computing, communications engineering, and intelligent systems.

This book consolidates the research relating to the security in SDN, CSDN, and Hybrid SDNs. The security enhancements derived from use of various SDN frameworks and the security challenges thus introduced, are also discussed. Overall, this book explains different architectures of SDNs and the security challenges needs for implementing them.

Software-Defined Networks (SDN) work by virtualization of the network and the Cognitive Software-Defined Network (CSDN) combines the efficiencies of SDN with cognitive learning algorithms and enhanced protocols to automatize SDN. Partial deployment of SDN along with traditional networking devices forms a Hybrid Software-Defined Network (HSDN). Software-Defined Network Frameworks: Security Issues and Use Cases consolidates the research relating to the security in SDN, CSDN, and Hybrid SDNs. The security enhancements derived from the use of various SDN frameworks and the security challenges thus introduced, are also discussed. Overall, this book explains the different architectures of SDNs and the security challenges needed for implementing them.

Features:

  • Illustrates different frameworks of SDN and their security issues in a single volume
  • Discusses design and assessment of efficient SDN northbound/southbound interfaces
  • Describes cognitive computing, affective computing, machine learning, and other novel tools
  • Illustrates coupling of SDN and traditional networking – Hybrid SDN
  • Explores services, technologies, algorithms, and methods for data analysis in CSDN

The book is aimed at researchers and graduate students in software engineering, network security, computer networks, high performance computing, communications engineering, and intelligent systems.

This book consolidates the research relating to the security in SDN, CSDN, and Hybrid SDNs. The security enhancements derived from use of various SDN frameworks and the security challenges thus introduced, are also discussed. Overall, this book explains different architectures of SDNs and the security challenges needs for implementing them.

Software-Defined Networks (SDN) work by virtualization of the network and the Cognitive Software-Defined Network (CSDN) combines the efficiencies of SDN with cognitive learning algorithms and enhanced protocols to automatize SDN. Partial deployment of SDN along with traditional networking devices forms a Hybrid Software-Defined Network (HSDN). Software-Defined Network Frameworks: Security Issues and Use Cases consolidates the research relating to the security in SDN, CSDN, and Hybrid SDNs. The security enhancements derived from the use of various SDN frameworks and the security challenges thus introduced, are also discussed. Overall, this book explains the different architectures of SDNs and the security challenges needed for implementing them.

Features:

  • Illustrates different frameworks of SDN and their security issues in a single volume
  • Discusses design and assessment of efficient SDN northbound/southbound interfaces
  • Describes cognitive computing, affective computing, machine learning, and other novel tools
  • Illustrates coupling of SDN and traditional networking – Hybrid SDN
  • Explores services, technologies, algorithms, and methods for data analysis in CSDN

The book is aimed at researchers and graduate students in software engineering, network security, computer networks, high performance computing, communications engineering, and intelligent systems.

This book consolidates the research relating to the security in SDN, CSDN, and Hybrid SDNs. The security enhancements derived from use of various SDN frameworks and the security challenges thus introduced, are also discussed. Overall, this book explains different architectures of SDNs and the security challenges needs for implementing them.

Software-Defined Networks (SDN) work by virtualization of the network and the Cognitive Software-Defined Network (CSDN) combines the efficiencies of SDN with cognitive learning algorithms and enhanced protocols to automatize SDN. Partial deployment of SDN along with traditional networking devices forms a Hybrid Software-Defined Network (HSDN). Software-Defined Network Frameworks: Security Issues and Use Cases consolidates the research relating to the security in SDN, CSDN, and Hybrid SDNs. The security enhancements derived from the use of various SDN frameworks and the security challenges thus introduced, are also discussed. Overall, this book explains the different architectures of SDNs and the security challenges needed for implementing them.

Features:

  • Illustrates different frameworks of SDN and their security issues in a single volume
  • Discusses design and assessment of efficient SDN northbound/southbound interfaces
  • Describes cognitive computing, affective computing, machine learning, and other novel tools
  • Illustrates coupling of SDN and traditional networking – Hybrid SDN
  • Explores services, technologies, algorithms, and methods for data analysis in CSDN

The book is aimed at researchers and graduate students in software engineering, network security, computer networks, high performance computing, communications engineering, and intelligent systems.

This book consolidates the research relating to the security in SDN, CSDN, and Hybrid SDNs. The security enhancements derived from use of various SDN frameworks and the security challenges thus introduced, are also discussed. Overall, this book explains different architectures of SDNs and the security challenges needs for implementing them.

Software-Defined Networks (SDN) work by virtualization of the network and the Cognitive Software-Defined Network (CSDN) combines the efficiencies of SDN with cognitive learning algorithms and enhanced protocols to automatize SDN. Partial deployment of SDN along with traditional networking devices forms a Hybrid Software-Defined Network (HSDN). Software-Defined Network Frameworks: Security Issues and Use Cases consolidates the research relating to the security in SDN, CSDN, and Hybrid SDNs. The security enhancements derived from the use of various SDN frameworks and the security challenges thus introduced, are also discussed. Overall, this book explains the different architectures of SDNs and the security challenges needed for implementing them.

Features:

  • Illustrates different frameworks of SDN and their security issues in a single volume
  • Discusses design and assessment of efficient SDN northbound/southbound interfaces
  • Describes cognitive computing, affective computing, machine learning, and other novel tools
  • Illustrates coupling of SDN and traditional networking – Hybrid SDN
  • Explores services, technologies, algorithms, and methods for data analysis in CSDN

The book is aimed at researchers and graduate students in software engineering, network security, computer networks, high performance computing, communications engineering, and intelligent systems.

This book consolidates the research relating to the security in SDN, CSDN, and Hybrid SDNs. The security enhancements derived from use of various SDN frameworks and the security challenges thus introduced, are also discussed. Overall, this book explains different architectures of SDNs and the security challenges needs for implementing them.

Software-Defined Networks (SDN) work by virtualization of the network and the Cognitive Software-Defined Network (CSDN) combines the efficiencies of SDN with cognitive learning algorithms and enhanced protocols to automatize SDN. Partial deployment of SDN along with traditional networking devices forms a Hybrid Software-Defined Network (HSDN). Software-Defined Network Frameworks: Security Issues and Use Cases consolidates the research relating to the security in SDN, CSDN, and Hybrid SDNs. The security enhancements derived from the use of various SDN frameworks and the security challenges thus introduced, are also discussed. Overall, this book explains the different architectures of SDNs and the security challenges needed for implementing them.

Features:

  • Illustrates different frameworks of SDN and their security issues in a single volume
  • Discusses design and assessment of efficient SDN northbound/southbound interfaces
  • Describes cognitive computing, affective computing, machine learning, and other novel tools
  • Illustrates coupling of SDN and traditional networking – Hybrid SDN
  • Explores services, technologies, algorithms, and methods for data analysis in CSDN

The book is aimed at researchers and graduate students in software engineering, network security, computer networks, high performance computing, communications engineering, and intelligent systems.

This book consolidates the research relating to the security in SDN, CSDN, and Hybrid SDNs. The security enhancements derived from use of various SDN frameworks and the security challenges thus introduced, are also discussed. Overall, this book explains different architectures of SDNs and the security challenges needs for implementing them.

Software-Defined Networks (SDN) work by virtualization of the network and the Cognitive Software-Defined Network (CSDN) combines the efficiencies of SDN with cognitive learning algorithms and enhanced protocols to automatize SDN. Partial deployment of SDN along with traditional networking devices forms a Hybrid Software-Defined Network (HSDN). Software-Defined Network Frameworks: Security Issues and Use Cases consolidates the research relating to the security in SDN, CSDN, and Hybrid SDNs. The security enhancements derived from the use of various SDN frameworks and the security challenges thus introduced, are also discussed. Overall, this book explains the different architectures of SDNs and the security challenges needed for implementing them.

Features:

  • Illustrates different frameworks of SDN and their security issues in a single volume
  • Discusses design and assessment of efficient SDN northbound/southbound interfaces
  • Describes cognitive computing, affective computing, machine learning, and other novel tools
  • Illustrates coupling of SDN and traditional networking – Hybrid SDN
  • Explores services, technologies, algorithms, and methods for data analysis in CSDN

The book is aimed at researchers and graduate students in software engineering, network security, computer networks, high performance computing, communications engineering, and intelligent systems.

This book consolidates the research relating to the security in SDN, CSDN, and Hybrid SDNs. The security enhancements derived from use of various SDN frameworks and the security challenges thus introduced, are also discussed. Overall, this book explains different architectures of SDNs and the security challenges needs for implementing them.

Software-Defined Networks (SDN) work by virtualization of the network and the Cognitive Software-Defined Network (CSDN) combines the efficiencies of SDN with cognitive learning algorithms and enhanced protocols to automatize SDN. Partial deployment of SDN along with traditional networking devices forms a Hybrid Software-Defined Network (HSDN). Software-Defined Network Frameworks: Security Issues and Use Cases consolidates the research relating to the security in SDN, CSDN, and Hybrid SDNs. The security enhancements derived from the use of various SDN frameworks and the security challenges thus introduced, are also discussed. Overall, this book explains the different architectures of SDNs and the security challenges needed for implementing them.

Features:

  • Illustrates different frameworks of SDN and their security issues in a single volume
  • Discusses design and assessment of efficient SDN northbound/southbound interfaces
  • Describes cognitive computing, affective computing, machine learning, and other novel tools
  • Illustrates coupling of SDN and traditional networking – Hybrid SDN
  • Explores services, technologies, algorithms, and methods for data analysis in CSDN

The book is aimed at researchers and graduate students in software engineering, network security, computer networks, high performance computing, communications engineering, and intelligent systems.

This book consolidates the research relating to the security in SDN, CSDN, and Hybrid SDNs. The security enhancements derived from use of various SDN frameworks and the security challenges thus introduced, are also discussed. Overall, this book explains different architectures of SDNs and the security challenges needs for implementing them.

Software-Defined Networks (SDN) work by virtualization of the network and the Cognitive Software-Defined Network (CSDN) combines the efficiencies of SDN with cognitive learning algorithms and enhanced protocols to automatize SDN. Partial deployment of SDN along with traditional networking devices forms a Hybrid Software-Defined Network (HSDN). Software-Defined Network Frameworks: Security Issues and Use Cases consolidates the research relating to the security in SDN, CSDN, and Hybrid SDNs. The security enhancements derived from the use of various SDN frameworks and the security challenges thus introduced, are also discussed. Overall, this book explains the different architectures of SDNs and the security challenges needed for implementing them.

Features:

  • Illustrates different frameworks of SDN and their security issues in a single volume
  • Discusses design and assessment of efficient SDN northbound/southbound interfaces
  • Describes cognitive computing, affective computing, machine learning, and other novel tools
  • Illustrates coupling of SDN and traditional networking – Hybrid SDN
  • Explores services, technologies, algorithms, and methods for data analysis in CSDN

The book is aimed at researchers and graduate students in software engineering, network security, computer networks, high performance computing, communications engineering, and intelligent systems.

This book consolidates the research relating to the security in SDN, CSDN, and Hybrid SDNs. The security enhancements derived from use of various SDN frameworks and the security challenges thus introduced, are also discussed. Overall, this book explains different architectures of SDNs and the security challenges needs for implementing them.

Software-Defined Networks (SDN) work by virtualization of the network and the Cognitive Software-Defined Network (CSDN) combines the efficiencies of SDN with cognitive learning algorithms and enhanced protocols to automatize SDN. Partial deployment of SDN along with traditional networking devices forms a Hybrid Software-Defined Network (HSDN). Software-Defined Network Frameworks: Security Issues and Use Cases consolidates the research relating to the security in SDN, CSDN, and Hybrid SDNs. The security enhancements derived from the use of various SDN frameworks and the security challenges thus introduced, are also discussed. Overall, this book explains the different architectures of SDNs and the security challenges needed for implementing them.

Features:

  • Illustrates different frameworks of SDN and their security issues in a single volume
  • Discusses design and assessment of efficient SDN northbound/southbound interfaces
  • Describes cognitive computing, affective computing, machine learning, and other novel tools
  • Illustrates coupling of SDN and traditional networking – Hybrid SDN
  • Explores services, technologies, algorithms, and methods for data analysis in CSDN

The book is aimed at researchers and graduate students in software engineering, network security, computer networks, high performance computing, communications engineering, and intelligent systems.

This book consolidates the research relating to the security in SDN, CSDN, and Hybrid SDNs. The security enhancements derived from use of various SDN frameworks and the security challenges thus introduced, are also discussed. Overall, this book explains different architectures of SDNs and the security challenges needs for implementing them.

Software-Defined Networks (SDN) work by virtualization of the network and the Cognitive Software-Defined Network (CSDN) combines the efficiencies of SDN with cognitive learning algorithms and enhanced protocols to automatize SDN. Partial deployment of SDN along with traditional networking devices forms a Hybrid Software-Defined Network (HSDN). Software-Defined Network Frameworks: Security Issues and Use Cases consolidates the research relating to the security in SDN, CSDN, and Hybrid SDNs. The security enhancements derived from the use of various SDN frameworks and the security challenges thus introduced, are also discussed. Overall, this book explains the different architectures of SDNs and the security challenges needed for implementing them.

Features:

  • Illustrates different frameworks of SDN and their security issues in a single volume
  • Discusses design and assessment of efficient SDN northbound/southbound interfaces
  • Describes cognitive computing, affective computing, machine learning, and other novel tools
  • Illustrates coupling of SDN and traditional networking – Hybrid SDN
  • Explores services, technologies, algorithms, and methods for data analysis in CSDN

The book is aimed at researchers and graduate students in software engineering, network security, computer networks, high performance computing, communications engineering, and intelligent systems.

This book consolidates the research relating to the security in SDN, CSDN, and Hybrid SDNs. The security enhancements derived from use of various SDN frameworks and the security challenges thus introduced, are also discussed. Overall, this book explains different architectures of SDNs and the security challenges needs for implementing them.

Software-Defined Networks (SDN) work by virtualization of the network and the Cognitive Software-Defined Network (CSDN) combines the efficiencies of SDN with cognitive learning algorithms and enhanced protocols to automatize SDN. Partial deployment of SDN along with traditional networking devices forms a Hybrid Software-Defined Network (HSDN). Software-Defined Network Frameworks: Security Issues and Use Cases consolidates the research relating to the security in SDN, CSDN, and Hybrid SDNs. The security enhancements derived from the use of various SDN frameworks and the security challenges thus introduced, are also discussed. Overall, this book explains the different architectures of SDNs and the security challenges needed for implementing them.

Features:

  • Illustrates different frameworks of SDN and their security issues in a single volume
  • Discusses design and assessment of efficient SDN northbound/southbound interfaces
  • Describes cognitive computing, affective computing, machine learning, and other novel tools
  • Illustrates coupling of SDN and traditional networking – Hybrid SDN
  • Explores services, technologies, algorithms, and methods for data analysis in CSDN

The book is aimed at researchers and graduate students in software engineering, network security, computer networks, high performance computing, communications engineering, and intelligent systems.

This book consolidates the research relating to the security in SDN, CSDN, and Hybrid SDNs. The security enhancements derived from use of various SDN frameworks and the security challenges thus introduced, are also discussed. Overall, this book explains different architectures of SDNs and the security challenges needs for implementing them.

Software-Defined Networks (SDN) work by virtualization of the network and the Cognitive Software-Defined Network (CSDN) combines the efficiencies of SDN with cognitive learning algorithms and enhanced protocols to automatize SDN. Partial deployment of SDN along with traditional networking devices forms a Hybrid Software-Defined Network (HSDN). Software-Defined Network Frameworks: Security Issues and Use Cases consolidates the research relating to the security in SDN, CSDN, and Hybrid SDNs. The security enhancements derived from the use of various SDN frameworks and the security challenges thus introduced, are also discussed. Overall, this book explains the different architectures of SDNs and the security challenges needed for implementing them.

Features:

  • Illustrates different frameworks of SDN and their security issues in a single volume
  • Discusses design and assessment of efficient SDN northbound/southbound interfaces
  • Describes cognitive computing, affective computing, machine learning, and other novel tools
  • Illustrates coupling of SDN and traditional networking – Hybrid SDN
  • Explores services, technologies, algorithms, and methods for data analysis in CSDN

The book is aimed at researchers and graduate students in software engineering, network security, computer networks, high performance computing, communications engineering, and intelligent systems.

This book consolidates the research relating to the security in SDN, CSDN, and Hybrid SDNs. The security enhancements derived from use of various SDN frameworks and the security challenges thus introduced, are also discussed. Overall, this book explains different architectures of SDNs and the security challenges needs for implementing them.

Software-Defined Networks (SDN) work by virtualization of the network and the Cognitive Software-Defined Network (CSDN) combines the efficiencies of SDN with cognitive learning algorithms and enhanced protocols to automatize SDN. Partial deployment of SDN along with traditional networking devices forms a Hybrid Software-Defined Network (HSDN). Software-Defined Network Frameworks: Security Issues and Use Cases consolidates the research relating to the security in SDN, CSDN, and Hybrid SDNs. The security enhancements derived from the use of various SDN frameworks and the security challenges thus introduced, are also discussed. Overall, this book explains the different architectures of SDNs and the security challenges needed for implementing them.

Features:

  • Illustrates different frameworks of SDN and their security issues in a single volume
  • Discusses design and assessment of efficient SDN northbound/southbound interfaces
  • Describes cognitive computing, affective computing, machine learning, and other novel tools
  • Illustrates coupling of SDN and traditional networking – Hybrid SDN
  • Explores services, technologies, algorithms, and methods for data analysis in CSDN

The book is aimed at researchers and graduate students in software engineering, network security, computer networks, high performance computing, communications engineering, and intelligent systems.

This book consolidates the research relating to the security in SDN, CSDN, and Hybrid SDNs. The security enhancements derived from use of various SDN frameworks and the security challenges thus introduced, are also discussed. Overall, this book explains different architectures of SDNs and the security challenges needs for implementing them.

Software-Defined Networks (SDN) work by virtualization of the network and the Cognitive Software-Defined Network (CSDN) combines the efficiencies of SDN with cognitive learning algorithms and enhanced protocols to automatize SDN. Partial deployment of SDN along with traditional networking devices forms a Hybrid Software-Defined Network (HSDN). Software-Defined Network Frameworks: Security Issues and Use Cases consolidates the research relating to the security in SDN, CSDN, and Hybrid SDNs. The security enhancements derived from the use of various SDN frameworks and the security challenges thus introduced, are also discussed. Overall, this book explains the different architectures of SDNs and the security challenges needed for implementing them.

Features:

  • Illustrates different frameworks of SDN and their security issues in a single volume
  • Discusses design and assessment of efficient SDN northbound/southbound interfaces
  • Describes cognitive computing, affective computing, machine learning, and other novel tools
  • Illustrates coupling of SDN and traditional networking – Hybrid SDN
  • Explores services, technologies, algorithms, and methods for data analysis in CSDN

The book is aimed at researchers and graduate students in software engineering, network security, computer networks, high performance computing, communications engineering, and intelligent systems.

This book consolidates the research relating to the security in SDN, CSDN, and Hybrid SDNs. The security enhancements derived from use of various SDN frameworks and the security challenges thus introduced, are also discussed. Overall, this book explains different architectures of SDNs and the security challenges needs for implementing them.

Software-Defined Networks (SDN) work by virtualization of the network and the Cognitive Software-Defined Network (CSDN) combines the efficiencies of SDN with cognitive learning algorithms and enhanced protocols to automatize SDN. Partial deployment of SDN along with traditional networking devices forms a Hybrid Software-Defined Network (HSDN). Software-Defined Network Frameworks: Security Issues and Use Cases consolidates the research relating to the security in SDN, CSDN, and Hybrid SDNs. The security enhancements derived from the use of various SDN frameworks and the security challenges thus introduced, are also discussed. Overall, this book explains the different architectures of SDNs and the security challenges needed for implementing them.

Features:

  • Illustrates different frameworks of SDN and their security issues in a single volume
  • Discusses design and assessment of efficient SDN northbound/southbound interfaces
  • Describes cognitive computing, affective computing, machine learning, and other novel tools
  • Illustrates coupling of SDN and traditional networking – Hybrid SDN
  • Explores services, technologies, algorithms, and methods for data analysis in CSDN

The book is aimed at researchers and graduate students in software engineering, network security, computer networks, high performance computing, communications engineering, and intelligent systems.

This book consolidates the research relating to the security in SDN, CSDN, and Hybrid SDNs. The security enhancements derived from use of various SDN frameworks and the security challenges thus introduced, are also discussed. Overall, this book explains different architectures of SDNs and the security challenges needs for implementing them.

Software-Defined Networks (SDN) work by virtualization of the network and the Cognitive Software-Defined Network (CSDN) combines the efficiencies of SDN with cognitive learning algorithms and enhanced protocols to automatize SDN. Partial deployment of SDN along with traditional networking devices forms a Hybrid Software-Defined Network (HSDN). Software-Defined Network Frameworks: Security Issues and Use Cases consolidates the research relating to the security in SDN, CSDN, and Hybrid SDNs. The security enhancements derived from the use of various SDN frameworks and the security challenges thus introduced, are also discussed. Overall, this book explains the different architectures of SDNs and the security challenges needed for implementing them.

Features:

  • Illustrates different frameworks of SDN and their security issues in a single volume
  • Discusses design and assessment of efficient SDN northbound/southbound interfaces
  • Describes cognitive computing, affective computing, machine learning, and other novel tools
  • Illustrates coupling of SDN and traditional networking – Hybrid SDN
  • Explores services, technologies, algorithms, and methods for data analysis in CSDN

The book is aimed at researchers and graduate students in software engineering, network security, computer networks, high performance computing, communications engineering, and intelligent systems.

This book consolidates the research relating to the security in SDN, CSDN, and Hybrid SDNs. The security enhancements derived from use of various SDN frameworks and the security challenges thus introduced, are also discussed. Overall, this book explains different architectures of SDNs and the security challenges needs for implementing them.

Software-Defined Networks (SDN) work by virtualization of the network and the Cognitive Software-Defined Network (CSDN) combines the efficiencies of SDN with cognitive learning algorithms and enhanced protocols to automatize SDN. Partial deployment of SDN along with traditional networking devices forms a Hybrid Software-Defined Network (HSDN). Software-Defined Network Frameworks: Security Issues and Use Cases consolidates the research relating to the security in SDN, CSDN, and Hybrid SDNs. The security enhancements derived from the use of various SDN frameworks and the security challenges thus introduced, are also discussed. Overall, this book explains the different architectures of SDNs and the security challenges needed for implementing them.

Features:

  • Illustrates different frameworks of SDN and their security issues in a single volume
  • Discusses design and assessment of efficient SDN northbound/southbound interfaces
  • Describes cognitive computing, affective computing, machine learning, and other novel tools
  • Illustrates coupling of SDN and traditional networking – Hybrid SDN
  • Explores services, technologies, algorithms, and methods for data analysis in CSDN

The book is aimed at researchers and graduate students in software engineering, network security, computer networks, high performance computing, communications engineering, and intelligent systems.

This book consolidates the research relating to the security in SDN, CSDN, and Hybrid SDNs. The security enhancements derived from use of various SDN frameworks and the security challenges thus introduced, are also discussed. Overall, this book explains different architectures of SDNs and the security challenges needs for implementing them.

Software-Defined Networks (SDN) work by virtualization of the network and the Cognitive Software-Defined Network (CSDN) combines the efficiencies of SDN with cognitive learning algorithms and enhanced protocols to automatize SDN. Partial deployment of SDN along with traditional networking devices forms a Hybrid Software-Defined Network (HSDN). Software-Defined Network Frameworks: Security Issues and Use Cases consolidates the research relating to the security in SDN, CSDN, and Hybrid SDNs. The security enhancements derived from the use of various SDN frameworks and the security challenges thus introduced, are also discussed. Overall, this book explains the different architectures of SDNs and the security challenges needed for implementing them.

Features:

  • Illustrates different frameworks of SDN and their security issues in a single volume
  • Discusses design and assessment of efficient SDN northbound/southbound interfaces
  • Describes cognitive computing, affective computing, machine learning, and other novel tools
  • Illustrates coupling of SDN and traditional networking – Hybrid SDN
  • Explores services, technologies, algorithms, and methods for data analysis in CSDN

The book is aimed at researchers and graduate students in software engineering, network security, computer networks, high performance computing, communications engineering, and intelligent systems.

This book consolidates the research relating to the security in SDN, CSDN, and Hybrid SDNs. The security enhancements derived from use of various SDN frameworks and the security challenges thus introduced, are also discussed. Overall, this book explains different architectures of SDNs and the security challenges needs for implementing them.

Software-Defined Networks (SDN) work by virtualization of the network and the Cognitive Software-Defined Network (CSDN) combines the efficiencies of SDN with cognitive learning algorithms and enhanced protocols to automatize SDN. Partial deployment of SDN along with traditional networking devices forms a Hybrid Software-Defined Network (HSDN). Software-Defined Network Frameworks: Security Issues and Use Cases consolidates the research relating to the security in SDN, CSDN, and Hybrid SDNs. The security enhancements derived from the use of various SDN frameworks and the security challenges thus introduced, are also discussed. Overall, this book explains the different architectures of SDNs and the security challenges needed for implementing them.

Features:

  • Illustrates different frameworks of SDN and their security issues in a single volume
  • Discusses design and assessment of efficient SDN northbound/southbound interfaces
  • Describes cognitive computing, affective computing, machine learning, and other novel tools
  • Illustrates coupling of SDN and traditional networking – Hybrid SDN
  • Explores services, technologies, algorithms, and methods for data analysis in CSDN

The book is aimed at researchers and graduate students in software engineering, network security, computer networks, high performance computing, communications engineering, and intelligent systems.

This book consolidates the research relating to the security in SDN, CSDN, and Hybrid SDNs. The security enhancements derived from use of various SDN frameworks and the security challenges thus introduced, are also discussed. Overall, this book explains different architectures of SDNs and the security challenges needs for implementing them.

Software-Defined Networks (SDN) work by virtualization of the network and the Cognitive Software-Defined Network (CSDN) combines the efficiencies of SDN with cognitive learning algorithms and enhanced protocols to automatize SDN. Partial deployment of SDN along with traditional networking devices forms a Hybrid Software-Defined Network (HSDN). Software-Defined Network Frameworks: Security Issues and Use Cases consolidates the research relating to the security in SDN, CSDN, and Hybrid SDNs. The security enhancements derived from the use of various SDN frameworks and the security challenges thus introduced, are also discussed. Overall, this book explains the different architectures of SDNs and the security challenges needed for implementing them.

Features:

  • Illustrates different frameworks of SDN and their security issues in a single volume
  • Discusses design and assessment of efficient SDN northbound/southbound interfaces
  • Describes cognitive computing, affective computing, machine learning, and other novel tools
  • Illustrates coupling of SDN and traditional networking – Hybrid SDN
  • Explores services, technologies, algorithms, and methods for data analysis in CSDN

The book is aimed at researchers and graduate students in software engineering, network security, computer networks, high performance computing, communications engineering, and intelligent systems.

This book consolidates the research relating to the security in SDN, CSDN, and Hybrid SDNs. The security enhancements derived from use of various SDN frameworks and the security challenges thus introduced, are also discussed. Overall, this book explains different architectures of SDNs and the security challenges needs for implementing them.

Software-Defined Networks (SDN) work by virtualization of the network and the Cognitive Software-Defined Network (CSDN) combines the efficiencies of SDN with cognitive learning algorithms and enhanced protocols to automatize SDN. Partial deployment of SDN along with traditional networking devices forms a Hybrid Software-Defined Network (HSDN). Software-Defined Network Frameworks: Security Issues and Use Cases consolidates the research relating to the security in SDN, CSDN, and Hybrid SDNs. The security enhancements derived from the use of various SDN frameworks and the security challenges thus introduced, are also discussed. Overall, this book explains the different architectures of SDNs and the security challenges needed for implementing them.

Features:

  • Illustrates different frameworks of SDN and their security issues in a single volume
  • Discusses design and assessment of efficient SDN northbound/southbound interfaces
  • Describes cognitive computing, affective computing, machine learning, and other novel tools
  • Illustrates coupling of SDN and traditional networking – Hybrid SDN
  • Explores services, technologies, algorithms, and methods for data analysis in CSDN

The book is aimed at researchers and graduate students in software engineering, network security, computer networks, high performance computing, communications engineering, and intelligent systems.

This book consolidates the research relating to the security in SDN, CSDN, and Hybrid SDNs. The security enhancements derived from use of various SDN frameworks and the security challenges thus introduced, are also discussed. Overall, this book explains different architectures of SDNs and the security challenges needs for implementing them.

Software-Defined Networks (SDN) work by virtualization of the network and the Cognitive Software-Defined Network (CSDN) combines the efficiencies of SDN with cognitive learning algorithms and enhanced protocols to automatize SDN. Partial deployment of SDN along with traditional networking devices forms a Hybrid Software-Defined Network (HSDN). Software-Defined Network Frameworks: Security Issues and Use Cases consolidates the research relating to the security in SDN, CSDN, and Hybrid SDNs. The security enhancements derived from the use of various SDN frameworks and the security challenges thus introduced, are also discussed. Overall, this book explains the different architectures of SDNs and the security challenges needed for implementing them.

Features:

  • Illustrates different frameworks of SDN and their security issues in a single volume
  • Discusses design and assessment of efficient SDN northbound/southbound interfaces
  • Describes cognitive computing, affective computing, machine learning, and other novel tools
  • Illustrates coupling of SDN and traditional networking – Hybrid SDN
  • Explores services, technologies, algorithms, and methods for data analysis in CSDN

The book is aimed at researchers and graduate students in software engineering, network security, computer networks, high performance computing, communications engineering, and intelligent systems.

This book consolidates the research relating to the security in SDN, CSDN, and Hybrid SDNs. The security enhancements derived from use of various SDN frameworks and the security challenges thus introduced, are also discussed. Overall, this book explains different architectures of SDNs and the security challenges needs for implementing them.

Software-Defined Networks (SDN) work by virtualization of the network and the Cognitive Software-Defined Network (CSDN) combines the efficiencies of SDN with cognitive learning algorithms and enhanced protocols to automatize SDN. Partial deployment of SDN along with traditional networking devices forms a Hybrid Software-Defined Network (HSDN). Software-Defined Network Frameworks: Security Issues and Use Cases consolidates the research relating to the security in SDN, CSDN, and Hybrid SDNs. The security enhancements derived from the use of various SDN frameworks and the security challenges thus introduced, are also discussed. Overall, this book explains the different architectures of SDNs and the security challenges needed for implementing them.

Features:

  • Illustrates different frameworks of SDN and their security issues in a single volume
  • Discusses design and assessment of efficient SDN northbound/southbound interfaces
  • Describes cognitive computing, affective computing, machine learning, and other novel tools
  • Illustrates coupling of SDN and traditional networking – Hybrid SDN
  • Explores services, technologies, algorithms, and methods for data analysis in CSDN

The book is aimed at researchers and graduate students in software engineering, network security, computer networks, high performance computing, communications engineering, and intelligent systems.

This book consolidates the research relating to the security in SDN, CSDN, and Hybrid SDNs. The security enhancements derived from use of various SDN frameworks and the security challenges thus introduced, are also discussed. Overall, this book explains different architectures of SDNs and the security challenges needs for implementing them.

Software-Defined Networks (SDN) work by virtualization of the network and the Cognitive Software-Defined Network (CSDN) combines the efficiencies of SDN with cognitive learning algorithms and enhanced protocols to automatize SDN. Partial deployment of SDN along with traditional networking devices forms a Hybrid Software-Defined Network (HSDN). Software-Defined Network Frameworks: Security Issues and Use Cases consolidates the research relating to the security in SDN, CSDN, and Hybrid SDNs. The security enhancements derived from the use of various SDN frameworks and the security challenges thus introduced, are also discussed. Overall, this book explains the different architectures of SDNs and the security challenges needed for implementing them.

Features:

  • Illustrates different frameworks of SDN and their security issues in a single volume
  • Discusses design and assessment of efficient SDN northbound/southbound interfaces
  • Describes cognitive computing, affective computing, machine learning, and other novel tools
  • Illustrates coupling of SDN and traditional networking – Hybrid SDN
  • Explores services, technologies, algorithms, and methods for data analysis in CSDN

The book is aimed at researchers and graduate students in software engineering, network security, computer networks, high performance computing, communications engineering, and intelligent systems.

This book consolidates the research relating to the security in SDN, CSDN, and Hybrid SDNs. The security enhancements derived from use of various SDN frameworks and the security challenges thus introduced, are also discussed. Overall, this book explains different architectures of SDNs and the security challenges needs for implementing them.

Software-Defined Networks (SDN) work by virtualization of the network and the Cognitive Software-Defined Network (CSDN) combines the efficiencies of SDN with cognitive learning algorithms and enhanced protocols to automatize SDN. Partial deployment of SDN along with traditional networking devices forms a Hybrid Software-Defined Network (HSDN). Software-Defined Network Frameworks: Security Issues and Use Cases consolidates the research relating to the security in SDN, CSDN, and Hybrid SDNs. The security enhancements derived from the use of various SDN frameworks and the security challenges thus introduced, are also discussed. Overall, this book explains the different architectures of SDNs and the security challenges needed for implementing them.

Features:

  • Illustrates different frameworks of SDN and their security issues in a single volume
  • Discusses design and assessment of efficient SDN northbound/southbound interfaces
  • Describes cognitive computing, affective computing, machine learning, and other novel tools
  • Illustrates coupling of SDN and traditional networking – Hybrid SDN
  • Explores services, technologies, algorithms, and methods for data analysis in CSDN

The book is aimed at researchers and graduate students in software engineering, network security, computer networks, high performance computing, communications engineering, and intelligent systems.

This book consolidates the research relating to the security in SDN, CSDN, and Hybrid SDNs. The security enhancements derived from use of various SDN frameworks and the security challenges thus introduced, are also discussed. Overall, this book explains different architectures of SDNs and the security challenges needs for implementing them.

Software-Defined Networks (SDN) work by virtualization of the network and the Cognitive Software-Defined Network (CSDN) combines the efficiencies of SDN with cognitive learning algorithms and enhanced protocols to automatize SDN. Partial deployment of SDN along with traditional networking devices forms a Hybrid Software-Defined Network (HSDN). Software-Defined Network Frameworks: Security Issues and Use Cases consolidates the research relating to the security in SDN, CSDN, and Hybrid SDNs. The security enhancements derived from the use of various SDN frameworks and the security challenges thus introduced, are also discussed. Overall, this book explains the different architectures of SDNs and the security challenges needed for implementing them.

Features:

  • Illustrates different frameworks of SDN and their security issues in a single volume
  • Discusses design and assessment of efficient SDN northbound/southbound interfaces
  • Describes cognitive computing, affective computing, machine learning, and other novel tools
  • Illustrates coupling of SDN and traditional networking – Hybrid SDN
  • Explores services, technologies, algorithms, and methods for data analysis in CSDN

The book is aimed at researchers and graduate students in software engineering, network security, computer networks, high performance computing, communications engineering, and intelligent systems.

This book consolidates the research relating to the security in SDN, CSDN, and Hybrid SDNs. The security enhancements derived from use of various SDN frameworks and the security challenges thus introduced, are also discussed. Overall, this book explains different architectures of SDNs and the security challenges needs for implementing them.

Software-Defined Networks (SDN) work by virtualization of the network and the Cognitive Software-Defined Network (CSDN) combines the efficiencies of SDN with cognitive learning algorithms and enhanced protocols to automatize SDN. Partial deployment of SDN along with traditional networking devices forms a Hybrid Software-Defined Network (HSDN). Software-Defined Network Frameworks: Security Issues and Use Cases consolidates the research relating to the security in SDN, CSDN, and Hybrid SDNs. The security enhancements derived from the use of various SDN frameworks and the security challenges thus introduced, are also discussed. Overall, this book explains the different architectures of SDNs and the security challenges needed for implementing them.

Features:

  • Illustrates different frameworks of SDN and their security issues in a single volume
  • Discusses design and assessment of efficient SDN northbound/southbound interfaces
  • Describes cognitive computing, affective computing, machine learning, and other novel tools
  • Illustrates coupling of SDN and traditional networking – Hybrid SDN
  • Explores services, technologies, algorithms, and methods for data analysis in CSDN

The book is aimed at researchers and graduate students in software engineering, network security, computer networks, high performance computing, communications engineering, and intelligent systems.

This book consolidates the research relating to the security in SDN, CSDN, and Hybrid SDNs. The security enhancements derived from use of various SDN frameworks and the security challenges thus introduced, are also discussed. Overall, this book explains different architectures of SDNs and the security challenges needs for implementing them.

Software-Defined Networks (SDN) work by virtualization of the network and the Cognitive Software-Defined Network (CSDN) combines the efficiencies of SDN with cognitive learning algorithms and enhanced protocols to automatize SDN. Partial deployment of SDN along with traditional networking devices forms a Hybrid Software-Defined Network (HSDN). Software-Defined Network Frameworks: Security Issues and Use Cases consolidates the research relating to the security in SDN, CSDN, and Hybrid SDNs. The security enhancements derived from the use of various SDN frameworks and the security challenges thus introduced, are also discussed. Overall, this book explains the different architectures of SDNs and the security challenges needed for implementing them.

Features:

  • Illustrates different frameworks of SDN and their security issues in a single volume
  • Discusses design and assessment of efficient SDN northbound/southbound interfaces
  • Describes cognitive computing, affective computing, machine learning, and other novel tools
  • Illustrates coupling of SDN and traditional networking – Hybrid SDN
  • Explores services, technologies, algorithms, and methods for data analysis in CSDN

The book is aimed at researchers and graduate students in software engineering, network security, computer networks, high performance computing, communications engineering, and intelligent systems.

This book consolidates the research relating to the security in SDN, CSDN, and Hybrid SDNs. The security enhancements derived from use of various SDN frameworks and the security challenges thus introduced, are also discussed. Overall, this book explains different architectures of SDNs and the security challenges needs for implementing them.

Software-Defined Networks (SDN) work by virtualization of the network and the Cognitive Software-Defined Network (CSDN) combines the efficiencies of SDN with cognitive learning algorithms and enhanced protocols to automatize SDN. Partial deployment of SDN along with traditional networking devices forms a Hybrid Software-Defined Network (HSDN). Software-Defined Network Frameworks: Security Issues and Use Cases consolidates the research relating to the security in SDN, CSDN, and Hybrid SDNs. The security enhancements derived from the use of various SDN frameworks and the security challenges thus introduced, are also discussed. Overall, this book explains the different architectures of SDNs and the security challenges needed for implementing them.

Features:

  • Illustrates different frameworks of SDN and their security issues in a single volume
  • Discusses design and assessment of efficient SDN northbound/southbound interfaces
  • Describes cognitive computing, affective computing, machine learning, and other novel tools
  • Illustrates coupling of SDN and traditional networking – Hybrid SDN
  • Explores services, technologies, algorithms, and methods for data analysis in CSDN

The book is aimed at researchers and graduate students in software engineering, network security, computer networks, high performance computing, communications engineering, and intelligent systems.

This book consolidates the research relating to the security in SDN, CSDN, and Hybrid SDNs. The security enhancements derived from use of various SDN frameworks and the security challenges thus introduced, are also discussed. Overall, this book explains different architectures of SDNs and the security challenges needs for implementing them.

Software-Defined Networks (SDN) work by virtualization of the network and the Cognitive Software-Defined Network (CSDN) combines the efficiencies of SDN with cognitive learning algorithms and enhanced protocols to automatize SDN. Partial deployment of SDN along with traditional networking devices forms a Hybrid Software-Defined Network (HSDN). Software-Defined Network Frameworks: Security Issues and Use Cases consolidates the research relating to the security in SDN, CSDN, and Hybrid SDNs. The security enhancements derived from the use of various SDN frameworks and the security challenges thus introduced, are also discussed. Overall, this book explains the different architectures of SDNs and the security challenges needed for implementing them.

Features:

  • Illustrates different frameworks of SDN and their security issues in a single volume
  • Discusses design and assessment of efficient SDN northbound/southbound interfaces
  • Describes cognitive computing, affective computing, machine learning, and other novel tools
  • Illustrates coupling of SDN and traditional networking – Hybrid SDN
  • Explores services, technologies, algorithms, and methods for data analysis in CSDN

The book is aimed at researchers and graduate students in software engineering, network security, computer networks, high performance computing, communications engineering, and intelligent systems.

This book consolidates the research relating to the security in SDN, CSDN, and Hybrid SDNs. The security enhancements derived from use of various SDN frameworks and the security challenges thus introduced, are also discussed. Overall, this book explains different architectures of SDNs and the security challenges needs for implementing them.

Software-Defined Networks (SDN) work by virtualization of the network and the Cognitive Software-Defined Network (CSDN) combines the efficiencies of SDN with cognitive learning algorithms and enhanced protocols to automatize SDN. Partial deployment of SDN along with traditional networking devices forms a Hybrid Software-Defined Network (HSDN). Software-Defined Network Frameworks: Security Issues and Use Cases consolidates the research relating to the security in SDN, CSDN, and Hybrid SDNs. The security enhancements derived from the use of various SDN frameworks and the security challenges thus introduced, are also discussed. Overall, this book explains the different architectures of SDNs and the security challenges needed for implementing them.

Features:

  • Illustrates different frameworks of SDN and their security issues in a single volume
  • Discusses design and assessment of efficient SDN northbound/southbound interfaces
  • Describes cognitive computing, affective computing, machine learning, and other novel tools
  • Illustrates coupling of SDN and traditional networking – Hybrid SDN
  • Explores services, technologies, algorithms, and methods for data analysis in CSDN

The book is aimed at researchers and graduate students in software engineering, network security, computer networks, high performance computing, communications engineering, and intelligent systems.

This book consolidates the research relating to the security in SDN, CSDN, and Hybrid SDNs. The security enhancements derived from use of various SDN frameworks and the security challenges thus introduced, are also discussed. Overall, this book explains different architectures of SDNs and the security challenges needs for implementing them.

Software-Defined Networks (SDN) work by virtualization of the network and the Cognitive Software-Defined Network (CSDN) combines the efficiencies of SDN with cognitive learning algorithms and enhanced protocols to automatize SDN. Partial deployment of SDN along with traditional networking devices forms a Hybrid Software-Defined Network (HSDN). Software-Defined Network Frameworks: Security Issues and Use Cases consolidates the research relating to the security in SDN, CSDN, and Hybrid SDNs. The security enhancements derived from the use of various SDN frameworks and the security challenges thus introduced, are also discussed. Overall, this book explains the different architectures of SDNs and the security challenges needed for implementing them.

Features:

  • Illustrates different frameworks of SDN and their security issues in a single volume
  • Discusses design and assessment of efficient SDN northbound/southbound interfaces
  • Describes cognitive computing, affective computing, machine learning, and other novel tools
  • Illustrates coupling of SDN and traditional networking – Hybrid SDN
  • Explores services, technologies, algorithms, and methods for data analysis in CSDN

The book is aimed at researchers and graduate students in software engineering, network security, computer networks, high performance computing, communications engineering, and intelligent systems.

This book consolidates the research relating to the security in SDN, CSDN, and Hybrid SDNs. The security enhancements derived from use of various SDN frameworks and the security challenges thus introduced, are also discussed. Overall, this book explains different architectures of SDNs and the security challenges needs for implementing them.

Software-Defined Networks (SDN) work by virtualization of the network and the Cognitive Software-Defined Network (CSDN) combines the efficiencies of SDN with cognitive learning algorithms and enhanced protocols to automatize SDN. Partial deployment of SDN along with traditional networking devices forms a Hybrid Software-Defined Network (HSDN). Software-Defined Network Frameworks: Security Issues and Use Cases consolidates the research relating to the security in SDN, CSDN, and Hybrid SDNs. The security enhancements derived from the use of various SDN frameworks and the security challenges thus introduced, are also discussed. Overall, this book explains the different architectures of SDNs and the security challenges needed for implementing them.

Features:

  • Illustrates different frameworks of SDN and their security issues in a single volume
  • Discusses design and assessment of efficient SDN northbound/southbound interfaces
  • Describes cognitive computing, affective computing, machine learning, and other novel tools
  • Illustrates coupling of SDN and traditional networking – Hybrid SDN
  • Explores services, technologies, algorithms, and methods for data analysis in CSDN

The book is aimed at researchers and graduate students in software engineering, network security, computer networks, high performance computing, communications engineering, and intelligent systems.

This book consolidates the research relating to the security in SDN, CSDN, and Hybrid SDNs. The security enhancements derived from use of various SDN frameworks and the security challenges thus introduced, are also discussed. Overall, this book explains different architectures of SDNs and the security challenges needs for implementing them.

Software-Defined Networks (SDN) work by virtualization of the network and the Cognitive Software-Defined Network (CSDN) combines the efficiencies of SDN with cognitive learning algorithms and enhanced protocols to automatize SDN. Partial deployment of SDN along with traditional networking devices forms a Hybrid Software-Defined Network (HSDN). Software-Defined Network Frameworks: Security Issues and Use Cases consolidates the research relating to the security in SDN, CSDN, and Hybrid SDNs. The security enhancements derived from the use of various SDN frameworks and the security challenges thus introduced, are also discussed. Overall, this book explains the different architectures of SDNs and the security challenges needed for implementing them.

Features:

  • Illustrates different frameworks of SDN and their security issues in a single volume
  • Discusses design and assessment of efficient SDN northbound/southbound interfaces
  • Describes cognitive computing, affective computing, machine learning, and other novel tools
  • Illustrates coupling of SDN and traditional networking – Hybrid SDN
  • Explores services, technologies, algorithms, and methods for data analysis in CSDN

The book is aimed at researchers and graduate students in software engineering, network security, computer networks, high performance computing, communications engineering, and intelligent systems.

This book consolidates the research relating to the security in SDN, CSDN, and Hybrid SDNs. The security enhancements derived from use of various SDN frameworks and the security challenges thus introduced, are also discussed. Overall, this book explains different architectures of SDNs and the security challenges needs for implementing them.

Software-Defined Networks (SDN) work by virtualization of the network and the Cognitive Software-Defined Network (CSDN) combines the efficiencies of SDN with cognitive learning algorithms and enhanced protocols to automatize SDN. Partial deployment of SDN along with traditional networking devices forms a Hybrid Software-Defined Network (HSDN). Software-Defined Network Frameworks: Security Issues and Use Cases consolidates the research relating to the security in SDN, CSDN, and Hybrid SDNs. The security enhancements derived from the use of various SDN frameworks and the security challenges thus introduced, are also discussed. Overall, this book explains the different architectures of SDNs and the security challenges needed for implementing them.

Features:

  • Illustrates different frameworks of SDN and their security issues in a single volume
  • Discusses design and assessment of efficient SDN northbound/southbound interfaces
  • Describes cognitive computing, affective computing, machine learning, and other novel tools
  • Illustrates coupling of SDN and traditional networking – Hybrid SDN
  • Explores services, technologies, algorithms, and methods for data analysis in CSDN

The book is aimed at researchers and graduate students in software engineering, network security, computer networks, high performance computing, communications engineering, and intelligent systems.

This book consolidates the research relating to the security in SDN, CSDN, and Hybrid SDNs. The security enhancements derived from use of various SDN frameworks and the security challenges thus introduced, are also discussed. Overall, this book explains different architectures of SDNs and the security challenges needs for implementing them.

Software-Defined Networks (SDN) work by virtualization of the network and the Cognitive Software-Defined Network (CSDN) combines the efficiencies of SDN with cognitive learning algorithms and enhanced protocols to automatize SDN. Partial deployment of SDN along with traditional networking devices forms a Hybrid Software-Defined Network (HSDN). Software-Defined Network Frameworks: Security Issues and Use Cases consolidates the research relating to the security in SDN, CSDN, and Hybrid SDNs. The security enhancements derived from the use of various SDN frameworks and the security challenges thus introduced, are also discussed. Overall, this book explains the different architectures of SDNs and the security challenges needed for implementing them.

Features:

  • Illustrates different frameworks of SDN and their security issues in a single volume
  • Discusses design and assessment of efficient SDN northbound/southbound interfaces
  • Describes cognitive computing, affective computing, machine learning, and other novel tools
  • Illustrates coupling of SDN and traditional networking – Hybrid SDN
  • Explores services, technologies, algorithms, and methods for data analysis in CSDN

The book is aimed at researchers and graduate students in software engineering, network security, computer networks, high performance computing, communications engineering, and intelligent systems.

This book consolidates the research relating to the security in SDN, CSDN, and Hybrid SDNs. The security enhancements derived from use of various SDN frameworks and the security challenges thus introduced, are also discussed. Overall, this book explains different architectures of SDNs and the security challenges needs for implementing them.

Software-Defined Networks (SDN) work by virtualization of the network and the Cognitive Software-Defined Network (CSDN) combines the efficiencies of SDN with cognitive learning algorithms and enhanced protocols to automatize SDN. Partial deployment of SDN along with traditional networking devices forms a Hybrid Software-Defined Network (HSDN). Software-Defined Network Frameworks: Security Issues and Use Cases consolidates the research relating to the security in SDN, CSDN, and Hybrid SDNs. The security enhancements derived from the use of various SDN frameworks and the security challenges thus introduced, are also discussed. Overall, this book explains the different architectures of SDNs and the security challenges needed for implementing them.

Features:

  • Illustrates different frameworks of SDN and their security issues in a single volume
  • Discusses design and assessment of efficient SDN northbound/southbound interfaces
  • Describes cognitive computing, affective computing, machine learning, and other novel tools
  • Illustrates coupling of SDN and traditional networking – Hybrid SDN
  • Explores services, technologies, algorithms, and methods for data analysis in CSDN

The book is aimed at researchers and graduate students in software engineering, network security, computer networks, high performance computing, communications engineering, and intelligent systems.

This book consolidates the research relating to the security in SDN, CSDN, and Hybrid SDNs. The security enhancements derived from use of various SDN frameworks and the security challenges thus introduced, are also discussed. Overall, this book explains different architectures of SDNs and the security challenges needs for implementing them.

Software-Defined Networks (SDN) work by virtualization of the network and the Cognitive Software-Defined Network (CSDN) combines the efficiencies of SDN with cognitive learning algorithms and enhanced protocols to automatize SDN. Partial deployment of SDN along with traditional networking devices forms a Hybrid Software-Defined Network (HSDN). Software-Defined Network Frameworks: Security Issues and Use Cases consolidates the research relating to the security in SDN, CSDN, and Hybrid SDNs. The security enhancements derived from the use of various SDN frameworks and the security challenges thus introduced, are also discussed. Overall, this book explains the different architectures of SDNs and the security challenges needed for implementing them.

Features:

  • Illustrates different frameworks of SDN and their security issues in a single volume
  • Discusses design and assessment of efficient SDN northbound/southbound interfaces
  • Describes cognitive computing, affective computing, machine learning, and other novel tools
  • Illustrates coupling of SDN and traditional networking – Hybrid SDN
  • Explores services, technologies, algorithms, and methods for data analysis in CSDN

The book is aimed at researchers and graduate students in software engineering, network security, computer networks, high performance computing, communications engineering, and intelligent systems.

This book consolidates the research relating to the security in SDN, CSDN, and Hybrid SDNs. The security enhancements derived from use of various SDN frameworks and the security challenges thus introduced, are also discussed. Overall, this book explains different architectures of SDNs and the security challenges needs for implementing them.

Software-Defined Networks (SDN) work by virtualization of the network and the Cognitive Software-Defined Network (CSDN) combines the efficiencies of SDN with cognitive learning algorithms and enhanced protocols to automatize SDN. Partial deployment of SDN along with traditional networking devices forms a Hybrid Software-Defined Network (HSDN). Software-Defined Network Frameworks: Security Issues and Use Cases consolidates the research relating to the security in SDN, CSDN, and Hybrid SDNs. The security enhancements derived from the use of various SDN frameworks and the security challenges thus introduced, are also discussed. Overall, this book explains the different architectures of SDNs and the security challenges needed for implementing them.

Features:

  • Illustrates different frameworks of SDN and their security issues in a single volume
  • Discusses design and assessment of efficient SDN northbound/southbound interfaces
  • Describes cognitive computing, affective computing, machine learning, and other novel tools
  • Illustrates coupling of SDN and traditional networking – Hybrid SDN
  • Explores services, technologies, algorithms, and methods for data analysis in CSDN

The book is aimed at researchers and graduate students in software engineering, network security, computer networks, high performance computing, communications engineering, and intelligent systems.

This book consolidates the research relating to the security in SDN, CSDN, and Hybrid SDNs. The security enhancements derived from use of various SDN frameworks and the security challenges thus introduced, are also discussed. Overall, this book explains different architectures of SDNs and the security challenges needs for implementing them.

Software-Defined Networks (SDN) work by virtualization of the network and the Cognitive Software-Defined Network (CSDN) combines the efficiencies of SDN with cognitive learning algorithms and enhanced protocols to automatize SDN. Partial deployment of SDN along with traditional networking devices forms a Hybrid Software-Defined Network (HSDN). Software-Defined Network Frameworks: Security Issues and Use Cases consolidates the research relating to the security in SDN, CSDN, and Hybrid SDNs. The security enhancements derived from the use of various SDN frameworks and the security challenges thus introduced, are also discussed. Overall, this book explains the different architectures of SDNs and the security challenges needed for implementing them.

Features:

  • Illustrates different frameworks of SDN and their security issues in a single volume
  • Discusses design and assessment of efficient SDN northbound/southbound interfaces
  • Describes cognitive computing, affective computing, machine learning, and other novel tools
  • Illustrates coupling of SDN and traditional networking – Hybrid SDN
  • Explores services, technologies, algorithms, and methods for data analysis in CSDN

The book is aimed at researchers and graduate students in software engineering, network security, computer networks, high performance computing, communications engineering, and intelligent systems.

This book consolidates the research relating to the security in SDN, CSDN, and Hybrid SDNs. The security enhancements derived from use of various SDN frameworks and the security challenges thus introduced, are also discussed. Overall, this book explains different architectures of SDNs and the security challenges needs for implementing them.

Software-Defined Networks (SDN) work by virtualization of the network and the Cognitive Software-Defined Network (CSDN) combines the efficiencies of SDN with cognitive learning algorithms and enhanced protocols to automatize SDN. Partial deployment of SDN along with traditional networking devices forms a Hybrid Software-Defined Network (HSDN). Software-Defined Network Frameworks: Security Issues and Use Cases consolidates the research relating to the security in SDN, CSDN, and Hybrid SDNs. The security enhancements derived from the use of various SDN frameworks and the security challenges thus introduced, are also discussed. Overall, this book explains the different architectures of SDNs and the security challenges needed for implementing them.

Features:

  • Illustrates different frameworks of SDN and their security issues in a single volume
  • Discusses design and assessment of efficient SDN northbound/southbound interfaces
  • Describes cognitive computing, affective computing, machine learning, and other novel tools
  • Illustrates coupling of SDN and traditional networking – Hybrid SDN
  • Explores services, technologies, algorithms, and methods for data analysis in CSDN

The book is aimed at researchers and graduate students in software engineering, network security, computer networks, high performance computing, communications engineering, and intelligent systems.

This book consolidates the research relating to the security in SDN, CSDN, and Hybrid SDNs. The security enhancements derived from use of various SDN frameworks and the security challenges thus introduced, are also discussed. Overall, this book explains different architectures of SDNs and the security challenges needs for implementing them.

Software-Defined Networks (SDN) work by virtualization of the network and the Cognitive Software-Defined Network (CSDN) combines the efficiencies of SDN with cognitive learning algorithms and enhanced protocols to automatize SDN. Partial deployment of SDN along with traditional networking devices forms a Hybrid Software-Defined Network (HSDN). Software-Defined Network Frameworks: Security Issues and Use Cases consolidates the research relating to the security in SDN, CSDN, and Hybrid SDNs. The security enhancements derived from the use of various SDN frameworks and the security challenges thus introduced, are also discussed. Overall, this book explains the different architectures of SDNs and the security challenges needed for implementing them.

Features:

  • Illustrates different frameworks of SDN and their security issues in a single volume
  • Discusses design and assessment of efficient SDN northbound/southbound interfaces
  • Describes cognitive computing, affective computing, machine learning, and other novel tools
  • Illustrates coupling of SDN and traditional networking – Hybrid SDN
  • Explores services, technologies, algorithms, and methods for data analysis in CSDN

The book is aimed at researchers and graduate students in software engineering, network security, computer networks, high performance computing, communications engineering, and intelligent systems.

This book consolidates the research relating to the security in SDN, CSDN, and Hybrid SDNs. The security enhancements derived from use of various SDN frameworks and the security challenges thus introduced, are also discussed. Overall, this book explains different architectures of SDNs and the security challenges needs for implementing them.

Software-Defined Networks (SDN) work by virtualization of the network and the Cognitive Software-Defined Network (CSDN) combines the efficiencies of SDN with cognitive learning algorithms and enhanced protocols to automatize SDN. Partial deployment of SDN along with traditional networking devices forms a Hybrid Software-Defined Network (HSDN). Software-Defined Network Frameworks: Security Issues and Use Cases consolidates the research relating to the security in SDN, CSDN, and Hybrid SDNs. The security enhancements derived from the use of various SDN frameworks and the security challenges thus introduced, are also discussed. Overall, this book explains the different architectures of SDNs and the security challenges needed for implementing them.

Features:

  • Illustrates different frameworks of SDN and their security issues in a single volume
  • Discusses design and assessment of efficient SDN northbound/southbound interfaces
  • Describes cognitive computing, affective computing, machine learning, and other novel tools
  • Illustrates coupling of SDN and traditional networking – Hybrid SDN
  • Explores services, technologies, algorithms, and methods for data analysis in CSDN

The book is aimed at researchers and graduate students in software engineering, network security, computer networks, high performance computing, communications engineering, and intelligent systems.

This book consolidates the research relating to the security in SDN, CSDN, and Hybrid SDNs. The security enhancements derived from use of various SDN frameworks and the security challenges thus introduced, are also discussed. Overall, this book explains different architectures of SDNs and the security challenges needs for implementing them.

Software-Defined Networks (SDN) work by virtualization of the network and the Cognitive Software-Defined Network (CSDN) combines the efficiencies of SDN with cognitive learning algorithms and enhanced protocols to automatize SDN. Partial deployment of SDN along with traditional networking devices forms a Hybrid Software-Defined Network (HSDN). Software-Defined Network Frameworks: Security Issues and Use Cases consolidates the research relating to the security in SDN, CSDN, and Hybrid SDNs. The security enhancements derived from the use of various SDN frameworks and the security challenges thus introduced, are also discussed. Overall, this book explains the different architectures of SDNs and the security challenges needed for implementing them.

Features:

  • Illustrates different frameworks of SDN and their security issues in a single volume
  • Discusses design and assessment of efficient SDN northbound/southbound interfaces
  • Describes cognitive computing, affective computing, machine learning, and other novel tools
  • Illustrates coupling of SDN and traditional networking – Hybrid SDN
  • Explores services, technologies, algorithms, and methods for data analysis in CSDN

The book is aimed at researchers and graduate students in software engineering, network security, computer networks, high performance computing, communications engineering, and intelligent systems.

This book consolidates the research relating to the security in SDN, CSDN, and Hybrid SDNs. The security enhancements derived from use of various SDN frameworks and the security challenges thus introduced, are also discussed. Overall, this book explains different architectures of SDNs and the security challenges needs for implementing them.

Software-Defined Networks (SDN) work by virtualization of the network and the Cognitive Software-Defined Network (CSDN) combines the efficiencies of SDN with cognitive learning algorithms and enhanced protocols to automatize SDN. Partial deployment of SDN along with traditional networking devices forms a Hybrid Software-Defined Network (HSDN). Software-Defined Network Frameworks: Security Issues and Use Cases consolidates the research relating to the security in SDN, CSDN, and Hybrid SDNs. The security enhancements derived from the use of various SDN frameworks and the security challenges thus introduced, are also discussed. Overall, this book explains the different architectures of SDNs and the security challenges needed for implementing them.

Features:

  • Illustrates different frameworks of SDN and their security issues in a single volume
  • Discusses design and assessment of efficient SDN northbound/southbound interfaces
  • Describes cognitive computing, affective computing, machine learning, and other novel tools
  • Illustrates coupling of SDN and traditional networking – Hybrid SDN
  • Explores services, technologies, algorithms, and methods for data analysis in CSDN

The book is aimed at researchers and graduate students in software engineering, network security, computer networks, high performance computing, communications engineering, and intelligent systems.

This book consolidates the research relating to the security in SDN, CSDN, and Hybrid SDNs. The security enhancements derived from use of various SDN frameworks and the security challenges thus introduced, are also discussed. Overall, this book explains different architectures of SDNs and the security challenges needs for implementing them.

Software-Defined Networks (SDN) work by virtualization of the network and the Cognitive Software-Defined Network (CSDN) combines the efficiencies of SDN with cognitive learning algorithms and enhanced protocols to automatize SDN. Partial deployment of SDN along with traditional networking devices forms a Hybrid Software-Defined Network (HSDN). Software-Defined Network Frameworks: Security Issues and Use Cases consolidates the research relating to the security in SDN, CSDN, and Hybrid SDNs. The security enhancements derived from the use of various SDN frameworks and the security challenges thus introduced, are also discussed. Overall, this book explains the different architectures of SDNs and the security challenges needed for implementing them.

Features:

  • Illustrates different frameworks of SDN and their security issues in a single volume
  • Discusses design and assessment of efficient SDN northbound/southbound interfaces
  • Describes cognitive computing, affective computing, machine learning, and other novel tools
  • Illustrates coupling of SDN and traditional networking – Hybrid SDN
  • Explores services, technologies, algorithms, and methods for data analysis in CSDN

The book is aimed at researchers and graduate students in software engineering, network security, computer networks, high performance computing, communications engineering, and intelligent systems.

This book consolidates the research relating to the security in SDN, CSDN, and Hybrid SDNs. The security enhancements derived from use of various SDN frameworks and the security challenges thus introduced, are also discussed. Overall, this book explains different architectures of SDNs and the security challenges needs for implementing them.

Software-Defined Networks (SDN) work by virtualization of the network and the Cognitive Software-Defined Network (CSDN) combines the efficiencies of SDN with cognitive learning algorithms and enhanced protocols to automatize SDN. Partial deployment of SDN along with traditional networking devices forms a Hybrid Software-Defined Network (HSDN). Software-Defined Network Frameworks: Security Issues and Use Cases consolidates the research relating to the security in SDN, CSDN, and Hybrid SDNs. The security enhancements derived from the use of various SDN frameworks and the security challenges thus introduced, are also discussed. Overall, this book explains the different architectures of SDNs and the security challenges needed for implementing them.

Features:

  • Illustrates different frameworks of SDN and their security issues in a single volume
  • Discusses design and assessment of efficient SDN northbound/southbound interfaces
  • Describes cognitive computing, affective computing, machine learning, and other novel tools
  • Illustrates coupling of SDN and traditional networking – Hybrid SDN
  • Explores services, technologies, algorithms, and methods for data analysis in CSDN

The book is aimed at researchers and graduate students in software engineering, network security, computer networks, high performance computing, communications engineering, and intelligent systems.

This book consolidates the research relating to the security in SDN, CSDN, and Hybrid SDNs. The security enhancements derived from use of various SDN frameworks and the security challenges thus introduced, are also discussed. Overall, this book explains different architectures of SDNs and the security challenges needs for implementing them.

Software-Defined Networks (SDN) work by virtualization of the network and the Cognitive Software-Defined Network (CSDN) combines the efficiencies of SDN with cognitive learning algorithms and enhanced protocols to automatize SDN. Partial deployment of SDN along with traditional networking devices forms a Hybrid Software-Defined Network (HSDN). Software-Defined Network Frameworks: Security Issues and Use Cases consolidates the research relating to the security in SDN, CSDN, and Hybrid SDNs. The security enhancements derived from the use of various SDN frameworks and the security challenges thus introduced, are also discussed. Overall, this book explains the different architectures of SDNs and the security challenges needed for implementing them.

Features:

  • Illustrates different frameworks of SDN and their security issues in a single volume
  • Discusses design and assessment of efficient SDN northbound/southbound interfaces
  • Describes cognitive computing, affective computing, machine learning, and other novel tools
  • Illustrates coupling of SDN and traditional networking – Hybrid SDN
  • Explores services, technologies, algorithms, and methods for data analysis in CSDN

The book is aimed at researchers and graduate students in software engineering, network security, computer networks, high performance computing, communications engineering, and intelligent systems.

This book consolidates the research relating to the security in SDN, CSDN, and Hybrid SDNs. The security enhancements derived from use of various SDN frameworks and the security challenges thus introduced, are also discussed. Overall, this book explains different architectures of SDNs and the security challenges needs for implementing them.

Software-Defined Networks (SDN) work by virtualization of the network and the Cognitive Software-Defined Network (CSDN) combines the efficiencies of SDN with cognitive learning algorithms and enhanced protocols to automatize SDN. Partial deployment of SDN along with traditional networking devices forms a Hybrid Software-Defined Network (HSDN). Software-Defined Network Frameworks: Security Issues and Use Cases consolidates the research relating to the security in SDN, CSDN, and Hybrid SDNs. The security enhancements derived from the use of various SDN frameworks and the security challenges thus introduced, are also discussed. Overall, this book explains the different architectures of SDNs and the security challenges needed for implementing them.

Features:

  • Illustrates different frameworks of SDN and their security issues in a single volume
  • Discusses design and assessment of efficient SDN northbound/southbound interfaces
  • Describes cognitive computing, affective computing, machine learning, and other novel tools
  • Illustrates coupling of SDN and traditional networking – Hybrid SDN
  • Explores services, technologies, algorithms, and methods for data analysis in CSDN

The book is aimed at researchers and graduate students in software engineering, network security, computer networks, high performance computing, communications engineering, and intelligent systems.

This book consolidates the research relating to the security in SDN, CSDN, and Hybrid SDNs. The security enhancements derived from use of various SDN frameworks and the security challenges thus introduced, are also discussed. Overall, this book explains different architectures of SDNs and the security challenges needs for implementing them.

Software-Defined Networks (SDN) work by virtualization of the network and the Cognitive Software-Defined Network (CSDN) combines the efficiencies of SDN with cognitive learning algorithms and enhanced protocols to automatize SDN. Partial deployment of SDN along with traditional networking devices forms a Hybrid Software-Defined Network (HSDN). Software-Defined Network Frameworks: Security Issues and Use Cases consolidates the research relating to the security in SDN, CSDN, and Hybrid SDNs. The security enhancements derived from the use of various SDN frameworks and the security challenges thus introduced, are also discussed. Overall, this book explains the different architectures of SDNs and the security challenges needed for implementing them.

Features:

  • Illustrates different frameworks of SDN and their security issues in a single volume
  • Discusses design and assessment of efficient SDN northbound/southbound interfaces
  • Describes cognitive computing, affective computing, machine learning, and other novel tools
  • Illustrates coupling of SDN and traditional networking – Hybrid SDN
  • Explores services, technologies, algorithms, and methods for data analysis in CSDN

The book is aimed at researchers and graduate students in software engineering, network security, computer networks, high performance computing, communications engineering, and intelligent systems.

This book consolidates the research relating to the security in SDN, CSDN, and Hybrid SDNs. The security enhancements derived from use of various SDN frameworks and the security challenges thus introduced, are also discussed. Overall, this book explains different architectures of SDNs and the security challenges needs for implementing them.

Software-Defined Networks (SDN) work by virtualization of the network and the Cognitive Software-Defined Network (CSDN) combines the efficiencies of SDN with cognitive learning algorithms and enhanced protocols to automatize SDN. Partial deployment of SDN along with traditional networking devices forms a Hybrid Software-Defined Network (HSDN). Software-Defined Network Frameworks: Security Issues and Use Cases consolidates the research relating to the security in SDN, CSDN, and Hybrid SDNs. The security enhancements derived from the use of various SDN frameworks and the security challenges thus introduced, are also discussed. Overall, this book explains the different architectures of SDNs and the security challenges needed for implementing them.

Features:

  • Illustrates different frameworks of SDN and their security issues in a single volume
  • Discusses design and assessment of efficient SDN northbound/southbound interfaces
  • Describes cognitive computing, affective computing, machine learning, and other novel tools
  • Illustrates coupling of SDN and traditional networking – Hybrid SDN
  • Explores services, technologies, algorithms, and methods for data analysis in CSDN

The book is aimed at researchers and graduate students in software engineering, network security, computer networks, high performance computing, communications engineering, and intelligent systems.

This book consolidates the research relating to the security in SDN, CSDN, and Hybrid SDNs. The security enhancements derived from use of various SDN frameworks and the security challenges thus introduced, are also discussed. Overall, this book explains different architectures of SDNs and the security challenges needs for implementing them.

Software-Defined Networks (SDN) work by virtualization of the network and the Cognitive Software-Defined Network (CSDN) combines the efficiencies of SDN with cognitive learning algorithms and enhanced protocols to automatize SDN. Partial deployment of SDN along with traditional networking devices forms a Hybrid Software-Defined Network (HSDN). Software-Defined Network Frameworks: Security Issues and Use Cases consolidates the research relating to the security in SDN, CSDN, and Hybrid SDNs. The security enhancements derived from the use of various SDN frameworks and the security challenges thus introduced, are also discussed. Overall, this book explains the different architectures of SDNs and the security challenges needed for implementing them.

Features:

  • Illustrates different frameworks of SDN and their security issues in a single volume
  • Discusses design and assessment of efficient SDN northbound/southbound interfaces
  • Describes cognitive computing, affective computing, machine learning, and other novel tools
  • Illustrates coupling of SDN and traditional networking – Hybrid SDN
  • Explores services, technologies, algorithms, and methods for data analysis in CSDN

The book is aimed at researchers and graduate students in software engineering, network security, computer networks, high performance computing, communications engineering, and intelligent systems.

This book consolidates the research relating to the security in SDN, CSDN, and Hybrid SDNs. The security enhancements derived from use of various SDN frameworks and the security challenges thus introduced, are also discussed. Overall, this book explains different architectures of SDNs and the security challenges needs for implementing them.

Software-Defined Networks (SDN) work by virtualization of the network and the Cognitive Software-Defined Network (CSDN) combines the efficiencies of SDN with cognitive learning algorithms and enhanced protocols to automatize SDN. Partial deployment of SDN along with traditional networking devices forms a Hybrid Software-Defined Network (HSDN). Software-Defined Network Frameworks: Security Issues and Use Cases consolidates the research relating to the security in SDN, CSDN, and Hybrid SDNs. The security enhancements derived from the use of various SDN frameworks and the security challenges thus introduced, are also discussed. Overall, this book explains the different architectures of SDNs and the security challenges needed for implementing them.

Features:

  • Illustrates different frameworks of SDN and their security issues in a single volume
  • Discusses design and assessment of efficient SDN northbound/southbound interfaces
  • Describes cognitive computing, affective computing, machine learning, and other novel tools
  • Illustrates coupling of SDN and traditional networking – Hybrid SDN
  • Explores services, technologies, algorithms, and methods for data analysis in CSDN

The book is aimed at researchers and graduate students in software engineering, network security, computer networks, high performance computing, communications engineering, and intelligent systems.

This book consolidates the research relating to the security in SDN, CSDN, and Hybrid SDNs. The security enhancements derived from use of various SDN frameworks and the security challenges thus introduced, are also discussed. Overall, this book explains different architectures of SDNs and the security challenges needs for implementing them.

Software-Defined Networks (SDN) work by virtualization of the network and the Cognitive Software-Defined Network (CSDN) combines the efficiencies of SDN with cognitive learning algorithms and enhanced protocols to automatize SDN. Partial deployment of SDN along with traditional networking devices forms a Hybrid Software-Defined Network (HSDN). Software-Defined Network Frameworks: Security Issues and Use Cases consolidates the research relating to the security in SDN, CSDN, and Hybrid SDNs. The security enhancements derived from the use of various SDN frameworks and the security challenges thus introduced, are also discussed. Overall, this book explains the different architectures of SDNs and the security challenges needed for implementing them.

Features:

  • Illustrates different frameworks of SDN and their security issues in a single volume
  • Discusses design and assessment of efficient SDN northbound/southbound interfaces
  • Describes cognitive computing, affective computing, machine learning, and other novel tools
  • Illustrates coupling of SDN and traditional networking – Hybrid SDN
  • Explores services, technologies, algorithms, and methods for data analysis in CSDN

The book is aimed at researchers and graduate students in software engineering, network security, computer networks, high performance computing, communications engineering, and intelligent systems.

This book consolidates the research relating to the security in SDN, CSDN, and Hybrid SDNs. The security enhancements derived from use of various SDN frameworks and the security challenges thus introduced, are also discussed. Overall, this book explains different architectures of SDNs and the security challenges needs for implementing them.

Software-Defined Networks (SDN) work by virtualization of the network and the Cognitive Software-Defined Network (CSDN) combines the efficiencies of SDN with cognitive learning algorithms and enhanced protocols to automatize SDN. Partial deployment of SDN along with traditional networking devices forms a Hybrid Software-Defined Network (HSDN). Software-Defined Network Frameworks: Security Issues and Use Cases consolidates the research relating to the security in SDN, CSDN, and Hybrid SDNs. The security enhancements derived from the use of various SDN frameworks and the security challenges thus introduced, are also discussed. Overall, this book explains the different architectures of SDNs and the security challenges needed for implementing them.

Features:

  • Illustrates different frameworks of SDN and their security issues in a single volume
  • Discusses design and assessment of efficient SDN northbound/southbound interfaces
  • Describes cognitive computing, affective computing, machine learning, and other novel tools
  • Illustrates coupling of SDN and traditional networking – Hybrid SDN
  • Explores services, technologies, algorithms, and methods for data analysis in CSDN

The book is aimed at researchers and graduate students in software engineering, network security, computer networks, high performance computing, communications engineering, and intelligent systems.

This book consolidates the research relating to the security in SDN, CSDN, and Hybrid SDNs. The security enhancements derived from use of various SDN frameworks and the security challenges thus introduced, are also discussed. Overall, this book explains different architectures of SDNs and the security challenges needs for implementing them.

Software-Defined Networks (SDN) work by virtualization of the network and the Cognitive Software-Defined Network (CSDN) combines the efficiencies of SDN with cognitive learning algorithms and enhanced protocols to automatize SDN. Partial deployment of SDN along with traditional networking devices forms a Hybrid Software-Defined Network (HSDN). Software-Defined Network Frameworks: Security Issues and Use Cases consolidates the research relating to the security in SDN, CSDN, and Hybrid SDNs. The security enhancements derived from the use of various SDN frameworks and the security challenges thus introduced, are also discussed. Overall, this book explains the different architectures of SDNs and the security challenges needed for implementing them.

Features:

  • Illustrates different frameworks of SDN and their security issues in a single volume
  • Discusses design and assessment of efficient SDN northbound/southbound interfaces
  • Describes cognitive computing, affective computing, machine learning, and other novel tools
  • Illustrates coupling of SDN and traditional networking – Hybrid SDN
  • Explores services, technologies, algorithms, and methods for data analysis in CSDN

The book is aimed at researchers and graduate students in software engineering, network security, computer networks, high performance computing, communications engineering, and intelligent systems.

This book consolidates the research relating to the security in SDN, CSDN, and Hybrid SDNs. The security enhancements derived from use of various SDN frameworks and the security challenges thus introduced, are also discussed. Overall, this book explains different architectures of SDNs and the security challenges needs for implementing them.

Software-Defined Networks (SDN) work by virtualization of the network and the Cognitive Software-Defined Network (CSDN) combines the efficiencies of SDN with cognitive learning algorithms and enhanced protocols to automatize SDN. Partial deployment of SDN along with traditional networking devices forms a Hybrid Software-Defined Network (HSDN). Software-Defined Network Frameworks: Security Issues and Use Cases consolidates the research relating to the security in SDN, CSDN, and Hybrid SDNs. The security enhancements derived from the use of various SDN frameworks and the security challenges thus introduced, are also discussed. Overall, this book explains the different architectures of SDNs and the security challenges needed for implementing them.

Features:

  • Illustrates different frameworks of SDN and their security issues in a single volume
  • Discusses design and assessment of efficient SDN northbound/southbound interfaces
  • Describes cognitive computing, affective computing, machine learning, and other novel tools
  • Illustrates coupling of SDN and traditional networking – Hybrid SDN
  • Explores services, technologies, algorithms, and methods for data analysis in CSDN

The book is aimed at researchers and graduate students in software engineering, network security, computer networks, high performance computing, communications engineering, and intelligent systems.

This book consolidates the research relating to the security in SDN, CSDN, and Hybrid SDNs. The security enhancements derived from use of various SDN frameworks and the security challenges thus introduced, are also discussed. Overall, this book explains different architectures of SDNs and the security challenges needs for implementing them.

Software-Defined Networks (SDN) work by virtualization of the network and the Cognitive Software-Defined Network (CSDN) combines the efficiencies of SDN with cognitive learning algorithms and enhanced protocols to automatize SDN. Partial deployment of SDN along with traditional networking devices forms a Hybrid Software-Defined Network (HSDN). Software-Defined Network Frameworks: Security Issues and Use Cases consolidates the research relating to the security in SDN, CSDN, and Hybrid SDNs. The security enhancements derived from the use of various SDN frameworks and the security challenges thus introduced, are also discussed. Overall, this book explains the different architectures of SDNs and the security challenges needed for implementing them.

Features:

  • Illustrates different frameworks of SDN and their security issues in a single volume
  • Discusses design and assessment of efficient SDN northbound/southbound interfaces
  • Describes cognitive computing, affective computing, machine learning, and other novel tools
  • Illustrates coupling of SDN and traditional networking – Hybrid SDN
  • Explores services, technologies, algorithms, and methods for data analysis in CSDN

The book is aimed at researchers and graduate students in software engineering, network security, computer networks, high performance computing, communications engineering, and intelligent systems.

This book consolidates the research relating to the security in SDN, CSDN, and Hybrid SDNs. The security enhancements derived from use of various SDN frameworks and the security challenges thus introduced, are also discussed. Overall, this book explains different architectures of SDNs and the security challenges needs for implementing them.

Software-Defined Networks (SDN) work by virtualization of the network and the Cognitive Software-Defined Network (CSDN) combines the efficiencies of SDN with cognitive learning algorithms and enhanced protocols to automatize SDN. Partial deployment of SDN along with traditional networking devices forms a Hybrid Software-Defined Network (HSDN). Software-Defined Network Frameworks: Security Issues and Use Cases consolidates the research relating to the security in SDN, CSDN, and Hybrid SDNs. The security enhancements derived from the use of various SDN frameworks and the security challenges thus introduced, are also discussed. Overall, this book explains the different architectures of SDNs and the security challenges needed for implementing them.

Features:

  • Illustrates different frameworks of SDN and their security issues in a single volume
  • Discusses design and assessment of efficient SDN northbound/southbound interfaces
  • Describes cognitive computing, affective computing, machine learning, and other novel tools
  • Illustrates coupling of SDN and traditional networking – Hybrid SDN
  • Explores services, technologies, algorithms, and methods for data analysis in CSDN

The book is aimed at researchers and graduate students in software engineering, network security, computer networks, high performance computing, communications engineering, and intelligent systems.

This book consolidates the research relating to the security in SDN, CSDN, and Hybrid SDNs. The security enhancements derived from use of various SDN frameworks and the security challenges thus introduced, are also discussed. Overall, this book explains different architectures of SDNs and the security challenges needs for implementing them.

Software-Defined Networks (SDN) work by virtualization of the network and the Cognitive Software-Defined Network (CSDN) combines the efficiencies of SDN with cognitive learning algorithms and enhanced protocols to automatize SDN. Partial deployment of SDN along with traditional networking devices forms a Hybrid Software-Defined Network (HSDN). Software-Defined Network Frameworks: Security Issues and Use Cases consolidates the research relating to the security in SDN, CSDN, and Hybrid SDNs. The security enhancements derived from the use of various SDN frameworks and the security challenges thus introduced, are also discussed. Overall, this book explains the different architectures of SDNs and the security challenges needed for implementing them.

Features:

  • Illustrates different frameworks of SDN and their security issues in a single volume
  • Discusses design and assessment of efficient SDN northbound/southbound interfaces
  • Describes cognitive computing, affective computing, machine learning, and other novel tools
  • Illustrates coupling of SDN and traditional networking – Hybrid SDN
  • Explores services, technologies, algorithms, and methods for data analysis in CSDN

The book is aimed at researchers and graduate students in software engineering, network security, computer networks, high performance computing, communications engineering, and intelligent systems.

This book consolidates the research relating to the security in SDN, CSDN, and Hybrid SDNs. The security enhancements derived from use of various SDN frameworks and the security challenges thus introduced, are also discussed. Overall, this book explains different architectures of SDNs and the security challenges needs for implementing them.

Software-Defined Networks (SDN) work by virtualization of the network and the Cognitive Software-Defined Network (CSDN) combines the efficiencies of SDN with cognitive learning algorithms and enhanced protocols to automatize SDN. Partial deployment of SDN along with traditional networking devices forms a Hybrid Software-Defined Network (HSDN). Software-Defined Network Frameworks: Security Issues and Use Cases consolidates the research relating to the security in SDN, CSDN, and Hybrid SDNs. The security enhancements derived from the use of various SDN frameworks and the security challenges thus introduced, are also discussed. Overall, this book explains the different architectures of SDNs and the security challenges needed for implementing them.

Features:

  • Illustrates different frameworks of SDN and their security issues in a single volume
  • Discusses design and assessment of efficient SDN northbound/southbound interfaces
  • Describes cognitive computing, affective computing, machine learning, and other novel tools
  • Illustrates coupling of SDN and traditional networking – Hybrid SDN
  • Explores services, technologies, algorithms, and methods for data analysis in CSDN

The book is aimed at researchers and graduate students in software engineering, network security, computer networks, high performance computing, communications engineering, and intelligent systems.

This book consolidates the research relating to the security in SDN, CSDN, and Hybrid SDNs. The security enhancements derived from use of various SDN frameworks and the security challenges thus introduced, are also discussed. Overall, this book explains different architectures of SDNs and the security challenges needs for implementing them.

Software-Defined Networks (SDN) work by virtualization of the network and the Cognitive Software-Defined Network (CSDN) combines the efficiencies of SDN with cognitive learning algorithms and enhanced protocols to automatize SDN. Partial deployment of SDN along with traditional networking devices forms a Hybrid Software-Defined Network (HSDN). Software-Defined Network Frameworks: Security Issues and Use Cases consolidates the research relating to the security in SDN, CSDN, and Hybrid SDNs. The security enhancements derived from the use of various SDN frameworks and the security challenges thus introduced, are also discussed. Overall, this book explains the different architectures of SDNs and the security challenges needed for implementing them.

Features:

  • Illustrates different frameworks of SDN and their security issues in a single volume
  • Discusses design and assessment of efficient SDN northbound/southbound interfaces
  • Describes cognitive computing, affective computing, machine learning, and other novel tools
  • Illustrates coupling of SDN and traditional networking – Hybrid SDN
  • Explores services, technologies, algorithms, and methods for data analysis in CSDN

The book is aimed at researchers and graduate students in software engineering, network security, computer networks, high performance computing, communications engineering, and intelligent systems.

This book consolidates the research relating to the security in SDN, CSDN, and Hybrid SDNs. The security enhancements derived from use of various SDN frameworks and the security challenges thus introduced, are also discussed. Overall, this book explains different architectures of SDNs and the security challenges needs for implementing them.

Software-Defined Networks (SDN) work by virtualization of the network and the Cognitive Software-Defined Network (CSDN) combines the efficiencies of SDN with cognitive learning algorithms and enhanced protocols to automatize SDN. Partial deployment of SDN along with traditional networking devices forms a Hybrid Software-Defined Network (HSDN). Software-Defined Network Frameworks: Security Issues and Use Cases consolidates the research relating to the security in SDN, CSDN, and Hybrid SDNs. The security enhancements derived from the use of various SDN frameworks and the security challenges thus introduced, are also discussed. Overall, this book explains the different architectures of SDNs and the security challenges needed for implementing them.

Features:

  • Illustrates different frameworks of SDN and their security issues in a single volume
  • Discusses design and assessment of efficient SDN northbound/southbound interfaces
  • Describes cognitive computing, affective computing, machine learning, and other novel tools
  • Illustrates coupling of SDN and traditional networking – Hybrid SDN
  • Explores services, technologies, algorithms, and methods for data analysis in CSDN

The book is aimed at researchers and graduate students in software engineering, network security, computer networks, high performance computing, communications engineering, and intelligent systems.

This book consolidates the research relating to the security in SDN, CSDN, and Hybrid SDNs. The security enhancements derived from use of various SDN frameworks and the security challenges thus introduced, are also discussed. Overall, this book explains different architectures of SDNs and the security challenges needs for implementing them.

Software-Defined Networks (SDN) work by virtualization of the network and the Cognitive Software-Defined Network (CSDN) combines the efficiencies of SDN with cognitive learning algorithms and enhanced protocols to automatize SDN. Partial deployment of SDN along with traditional networking devices forms a Hybrid Software-Defined Network (HSDN). Software-Defined Network Frameworks: Security Issues and Use Cases consolidates the research relating to the security in SDN, CSDN, and Hybrid SDNs. The security enhancements derived from the use of various SDN frameworks and the security challenges thus introduced, are also discussed. Overall, this book explains the different architectures of SDNs and the security challenges needed for implementing them.

Features:

  • Illustrates different frameworks of SDN and their security issues in a single volume
  • Discusses design and assessment of efficient SDN northbound/southbound interfaces
  • Describes cognitive computing, affective computing, machine learning, and other novel tools
  • Illustrates coupling of SDN and traditional networking – Hybrid SDN
  • Explores services, technologies, algorithms, and methods for data analysis in CSDN

The book is aimed at researchers and graduate students in software engineering, network security, computer networks, high performance computing, communications engineering, and intelligent systems.

This book consolidates the research relating to the security in SDN, CSDN, and Hybrid SDNs. The security enhancements derived from use of various SDN frameworks and the security challenges thus introduced, are also discussed. Overall, this book explains different architectures of SDNs and the security challenges needs for implementing them.

Software-Defined Networks (SDN) work by virtualization of the network and the Cognitive Software-Defined Network (CSDN) combines the efficiencies of SDN with cognitive learning algorithms and enhanced protocols to automatize SDN. Partial deployment of SDN along with traditional networking devices forms a Hybrid Software-Defined Network (HSDN). Software-Defined Network Frameworks: Security Issues and Use Cases consolidates the research relating to the security in SDN, CSDN, and Hybrid SDNs. The security enhancements derived from the use of various SDN frameworks and the security challenges thus introduced, are also discussed. Overall, this book explains the different architectures of SDNs and the security challenges needed for implementing them.

Features:

  • Illustrates different frameworks of SDN and their security issues in a single volume
  • Discusses design and assessment of efficient SDN northbound/southbound interfaces
  • Describes cognitive computing, affective computing, machine learning, and other novel tools
  • Illustrates coupling of SDN and traditional networking – Hybrid SDN
  • Explores services, technologies, algorithms, and methods for data analysis in CSDN

The book is aimed at researchers and graduate students in software engineering, network security, computer networks, high performance computing, communications engineering, and intelligent systems.

This book consolidates the research relating to the security in SDN, CSDN, and Hybrid SDNs. The security enhancements derived from use of various SDN frameworks and the security challenges thus introduced, are also discussed. Overall, this book explains different architectures of SDNs and the security challenges needs for implementing them.

Software-Defined Networks (SDN) work by virtualization of the network and the Cognitive Software-Defined Network (CSDN) combines the efficiencies of SDN with cognitive learning algorithms and enhanced protocols to automatize SDN. Partial deployment of SDN along with traditional networking devices forms a Hybrid Software-Defined Network (HSDN). Software-Defined Network Frameworks: Security Issues and Use Cases consolidates the research relating to the security in SDN, CSDN, and Hybrid SDNs. The security enhancements derived from the use of various SDN frameworks and the security challenges thus introduced, are also discussed. Overall, this book explains the different architectures of SDNs and the security challenges needed for implementing them.

Features:

  • Illustrates different frameworks of SDN and their security issues in a single volume
  • Discusses design and assessment of efficient SDN northbound/southbound interfaces
  • Describes cognitive computing, affective computing, machine learning, and other novel tools
  • Illustrates coupling of SDN and traditional networking – Hybrid SDN
  • Explores services, technologies, algorithms, and methods for data analysis in CSDN

The book is aimed at researchers and graduate students in software engineering, network security, computer networks, high performance computing, communications engineering, and intelligent systems.

This book consolidates the research relating to the security in SDN, CSDN, and Hybrid SDNs. The security enhancements derived from use of various SDN frameworks and the security challenges thus introduced, are also discussed. Overall, this book explains different architectures of SDNs and the security challenges needs for implementing them.

Software-Defined Networks (SDN) work by virtualization of the network and the Cognitive Software-Defined Network (CSDN) combines the efficiencies of SDN with cognitive learning algorithms and enhanced protocols to automatize SDN. Partial deployment of SDN along with traditional networking devices forms a Hybrid Software-Defined Network (HSDN). Software-Defined Network Frameworks: Security Issues and Use Cases consolidates the research relating to the security in SDN, CSDN, and Hybrid SDNs. The security enhancements derived from the use of various SDN frameworks and the security challenges thus introduced, are also discussed. Overall, this book explains the different architectures of SDNs and the security challenges needed for implementing them.

Features:

  • Illustrates different frameworks of SDN and their security issues in a single volume
  • Discusses design and assessment of efficient SDN northbound/southbound interfaces
  • Describes cognitive computing, affective computing, machine learning, and other novel tools
  • Illustrates coupling of SDN and traditional networking – Hybrid SDN
  • Explores services, technologies, algorithms, and methods for data analysis in CSDN

The book is aimed at researchers and graduate students in software engineering, network security, computer networks, high performance computing, communications engineering, and intelligent systems.


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