Author(s) Name: Fadi Al-Turjman, B.D. Deebak
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.
Table of Contents
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
ISBN: 9780128216033
Publisher: Elsevier Science & Technology Books
Year of Publication: 2020
Book Link: Home Page Url
