Software-Defined Network Frameworks
GBP 110.00
Kattintson ide a feliratkozáshoz
| ISBN13: | 9781032450223 |
| ISBN10: | 1032450223 |
| Kötéstípus: | Keménykötés |
| Terjedelem: | 324 oldal |
| Méret: | 234x156 mm |
| Súly: | 760 g |
| Nyelv: | angol |
| Illusztrációk: | 101 Illustrations, black & white; 14 Halftones, black & white; 87 Line drawings, black & white; 19 Tables, black & white |
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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.
1.A System Model of Fault Tolerance Technique in Distributed System and Scalable System Using Machine Learning
2.An Overview of Software-Defined Network Frameworks
3.Security issues in Software Defined Networks & its Solutions
4.Importance of Dynamic Load Balancing and Virtualization role in Dynamic Load Balancing
5.Predicting Consumer Behaviours with Data Analytics for Decision Making
6.Software-Defined Networking (SDN): Revolutionizing Network Infrastructure for the Future
7.Software-Defined Network: Security Solutions, Applications and Future
8.Multi-Hop Routing Protocol in SDN-Based Wireless Sensor Network: A Comprehensive Survey
9.Performance Analysis of Load Balancing Algorithm with Cloud Computing- A Survey
10.Comprehensive Survey of Implementing Multiple Controllers In A Software Defined Network
11.Control Plane Security Issues in Software Defined Networking: A Comprehensive Review
12.Assessment on Role of IoT in Electronic Banking Industry
13.Investigation on SDN Attacks and Solutions in 5G Mobile Network
14.Designing Intrusion Detection Systems for Software Defined Networks using Deep Learning/Machine Learning Techniques
15.The Essence of Software Defined Network in Big Data Analytics
16.TCPFlood Defender: TCP SYN Flood Attacks Detection in SDN Environment Using Statistical and Ensemble Machine Learning Methods