About the Book
This book covers the security challenges of software-defined networks and proposes innovative solutions, such as the decentralization of security services and integration with blockchain technology, to enhance software-defined network security. It includes multiple case studies demonstrating the effectiveness of decentralized software-defined network security with three layered architectures including all application programming interfaces.
This book:
Offers in-depth analysis of software-defined network protocols including OpenFlow, Border Gateway Protocol Link-State (BGP-LS), and Network Configuration Protocol (NETCONF).
Provides practical guidelines for implementing security measures within software-defined network environments, with a focus on technical aspects like firewall rules, intrusion detection, and access control policies.
Explores how blockchain can be integrated into software-defined networks to enhance security, providing step-by-step technical guidance for implementation.
Discusses supply chain transparency with integration of blockchain and software-defined networks.
Explains blockchain-enhanced network monitoring and control, and implementation of blockchain-secured network communication.
It is primarily written for senior undergraduates, graduate students, and academic researchers in diverse fields including electrical engineering, electronics and communications engineering, computer science and engineering, and information technology.
Table of Contents:
1. Basics of blockchain technology and its underlying principles. 2. Revolutionizing Network Architecture: The Promise and Potential of Software Defined Networking. 3. Navigating Scalability: Insights into Blockchain Enabled SDN Environment. 4. Impact of DDoS Attack on Cloud Enabled Networks. 5. Security Revolution for Transforming Network with Blockchain Driven SDN. 6. Blockchain Technology: Transforming the Financial Services Landscape for Banks of the Future. 7. Blockchain disruptive role for empowering Cyber Security. 8. Improving the quality of service of application with Big Data & SDN. 9. Usage of AI and Machine Learning Techniques for Solving Potential Problems in Networks Using SDN.
About the Author :
Sarvesh Tanwar is Professor at Amity Institute of Information Technology (AIIT), Amity University, Noida. She is head of AUN Blockchain & Data Security Research Lab. She has Completed her M.Tech (CSE) degree from MMU, Mullana and Ph.D in (CSE) from Mody University, Laxmangarh (Raj.). She has more than 15 years of teaching and research experience. Her area of research includes Public Key Infrastructure (PKI), Cryptography, Blockchain and Cyber Security. She has published more than 100 research papers in International Journals (SCI/Scopus/WoS and Peer -Review) and Conferences. She is currently guiding six PhD scholars and has supervised 1 PhD Scholar & 5 M.Tech Research scholars. She has filed 22 patents (8 Granted) and 2 copyrights in the relevant field. She is Senior member IEEE, Life - Member, Cryptology Research Society of India (CRSI), Indian Institute of Statistics, Kolkata, India and member of International Association of Computer Science and Information Technology (IACSIT), Singapore. She is a Member of the Editorial Board of the International Journal of Sensors, Wireless Communications and Control, Bentham Science.
Sumit Badotra is currently serving as a Postdoctoral Research Fellow at the Department of Electrical and Computer Engineering, National University of Singapore (NUS), Singapore. He received his Ph.D. in Computer Science and Engineering from Chitkara University, India, under a DST-Government of India-funded project, where his research focused on Software-Defined Networking (SDN) security and anomaly detection frameworks. He has also held academic positions at various universities contributing to both teaching and funded research activities. Dr. Badotra has authored and co-authored several research papers published in high-impact international journals and conferences. His research interests include SDN security, network anomaly detection, distributed architectures, machine learning, and cloud computing. He has also worked on real-time frameworks for DDoS mitigation, adaptive ML-based security solutions, and hybrid privacy-preserving architectures. He actively contributes as a reviewer and editorial board member for various international journals and conferences in the field of computer networks and cybersecurity. Dr. Badotra holds multiple patents and has received best paper and presentation awards for his contributions to network security research.
Harish Garg received a Ph.D. degree in applied mathematics with a specialization in Reliability theory and soft computing techniques from IIT Roorkee, India, in 2013. Presently, he is working with School of Mathematics at Thapar Institute of Engineering & Technology (Deemed University) Patiala, Punjab, India. He has authored over 280 papers (with SCI papers 240) published in refereed International Journals and has supervised 07 Ph.D. dissertations. His work published including Information Sciences, IEEE Transactions on Fuzzy Systems, International Journal of Intelligent Systems, IEEE/CAA Journal Of Automatic Sinica, IEEE Transactions On Emerging Topics In Computational Intelligence, Cognitive Computation, Artificial Intelligence Review, Applied Intelligence, and many more. He is the recipient of the Top-Cited Paper by India-based Author (2015 – 2019) from a reputed Publisher. He serves as Editor-in-Chief of Annals of Optimization Theory and Practice. He is also the Associate Editors for several renowned journals such as Journal of Intelligent & Fuzzy Systems, Kybernetes, Mathematical Problems in Engineering, Journal of Industrial & Management Optimization, International Journal of Computational and Intelligence Systems, Complexity, Complex and Intelligent Systems etc. His Google citations are over 9540 with h-index is 57. His research interests are in the fields of Computational Intelligence, Reliability analysis, multi-criteria decision making, fuzzy decision making, Pythagorean fuzzy sets, Computing with words and Soft Computing.
