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Security in IoT Social Networks. Intelligent Data-Centric Systems: Sensor Collected Intelligence

  • ID: 5018894
  • Book
  • October 2020
  • Region: Global
  • 320 Pages
  • Elsevier Science and Technology
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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.

  • Provides several characteristics of social, network, and physical security associated with social information networks
  • Presents the security mechanisms and events related to social information networks
  • Covers emerging topics, such as network information structures like on-line social networks, heterogeneous and homogeneous information networks, and modern information networks
  • Includes smart solutions based on artificial intelligence, machine learning, and deep learning for enhancing the performance of social information network security protocols and models
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1. Security Issues and Technical Challenges in IoT-enabled Social Networks
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
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Al-Turjman, Fadi
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.
Deebak, B.D.
B.D Deebak is presently working as Associate Professor in the department of Computational Intelligence, School of Computer Science and Engineering at Vellore Institute of Technology, Vellore, India. He previously associated with GMR Institute of Technology, Rajam (AP) as Associate Professor in the Department of Computer Science and Engineering. He also associated with Middle East Technical University (METU) Northern Cyprus Campus during 2016-2017. He has more than 12 Years of Teaching Experience, Research in various Engineering Institutions in India and Abroad. He has published 22 papers in well reputed publishers such as IEEE, Elsevier, Springer and Tubitak.
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