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

Features:

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

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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Yes, you can access Software-Defined Network Frameworks by Mandeep Kaur,Vishal Jain,Parma Nand,Nitin Rakesh in PDF and/or ePUB format, as well as other popular books in Technology & Engineering & Electrical Engineering & Telecommunications. We have over one million books available in our catalogue for you to explore.

Information

Publisher

Year

Print ISBN

eBook ISBN

Edition

Topic

Technology & Engineering

Subtopic

Electrical Engineering & Telecommunications

Index

Technology & Engineering

Cover
Half Title
Series Page
Title Page
Copyright Page
Table of Contents
Preface
Editors
List of Contributors
Chapter 1 A System Model of Fault Tolerance Technique in Distributed System and Scalable System Using Machine Learning
Chapter 2 An Overview of Software-Defined Network (SDN) Frameworks
Chapter 3 Security Issues in Software-Defined Networks and Its Solutions
Chapter 4 Importance of Dynamic Load Balancing and Virtualization Role in Dynamic Load Balancing
Chapter 5 Predicting Consumer Behaviors with Data Analytics for Decision-Making
Chapter 6 Software-Defined Networking (SDN): Revolutionizing Network Infrastructure for the Future
Chapter 7 Software-Defined Network: Security Solutions, Applications, and Future
Chapter 8 Multi-Hop Routing Protocol in SDN-Based Wireless Sensor Network: A Comprehensive Survey
Chapter 9 Performance Analysis of Load Balancing Algorithm with Cloud Computing: A Survey
Chapter 10 Comprehensive Survey of Implementing Multiple Controllers in a Software-Defined Network (SDN)
Chapter 11 Control Plane Security Issues in Software-Defined Networking: A Comprehensive Review
Chapter 12 Assessment of the Role of IoT in Electronic Banking Industry
Chapter 13 Investigation of SDN Attacks and Solutions in 5G Mobile Network
Chapter 14 Designing Intrusion Detection Systems for Software-Defined Networks Using Deep Learning/Machine Learning Techniques
Chapter 15 The Essence of Software-Defined Network in Big Data Analytics
Chapter 16 TCPFlood Defender: TCP SYN Flood Attacks Detection in SDN Environment Using Statistical and Ensemble Machine Learning Methods
Index

About this book

Frequently asked questions

Information

Table of contents