Security in IoT Social Networks takes a deep dive into security threats and risks, focusing on real-world social and financial effects. Mining and analyzing enormously vast networks is a vital part of exploiting Big Data. This book provides insight into the technological aspects of modeling, searching, and mining for corresponding research issues, as well as designing and analyzing models for resolving such challenges. The book will help start-ups grow, providing research directions concerning security mechanisms and protocols for social information networks. The book covers structural analysis of large social information networks, elucidating models and algorithms and their fundamental properties.
Moreover, this book includes smart solutions based on artificial intelligence, machine learning, and deep learning for enhancing the performance of social information network security protocols and models. This book is a detailed reference for academicians, professionals, and young researchers. The wide range of topics provides extensive information and data for future research challenges in present-day social information networks.
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2. Emerging Social IoT Applications and Security Assurance
3. Optimized Security Models and deep learning for Social IoT Networks
4. Key Agreement and Social IoT networks
5. Biometrics and Authentication Methods in the IoT Era
6. Forensic Analysis in Social IoT Applications
7. Recommended IoT Systems
Security Threats and Mechanisms
8. Enabling Cyber-Physical Technologies for Social IoT Networks
9. Deception Detection for Fake Injections in IoT Networks
10. Social Networking for medical and health care application
Prof. Dr. Fadi Al-Turjman received his Ph.D. in computer science from Queen's University, Canada, in 2011. He is a full professor and a research center director at Near East University, Nicosia. Prof. Al-Turjman is a leading authority in the areas of smart/intelligent, wireless, and mobile networks. His publication spans over 250 publications in journals, conferences, patents, and books, in addition to numerous keynotes and plenary talks at flagship venues. He also received the prestigious Best Research Paper Award from Elsevier Computer Communications Journal for the period 2015-2018, in addition to the Top Researcher Award for 2018 at Antalya Bilim University, Turkey.
B.D. Deebak Associate Professor, Department of Computational Intelligence, School of Computer Science and Engineering, Vellor Institute of Technology, Vellore, Tamil Nadu, India.
Assoc. Prof. B.D. Deebak is Associate Professor in the department of Computational Intelligence, School of Computer Science and Engineering at Vellore Institute of Technology, Vellore. Previously he was at GMR Institute of Technology, Rajam (AP) as Associate Professor in the Department of Computer Science and Engineering and before that Middle East Technical University (METU) Northern Cyprus Campus. He has more than 12 Years of Teaching Experience, Research in various Engineering Institutions. His areas of research include Multimedia Networks, Network Security and Machine Learning. He is an active member in IE (I), CSI and ISTE. His current research interests include computer networks, wireless communication systems, wireless sensor networks, Multimedia Networks, Routing and Security. He has published 12 papers in well reputed publishers such as IEEE, Springer and Tubitak. He also serves as reviewer from IEEE Communications Letters, IEEE Access, IEEE System and IEEE Sensor Journal.