Security in Iot Social Networks

Erscheinungsjahr 2020
ISBN: 978-0-12-821599-9
Verlag: ACADEMIC PR INC

Buch, Englisch, 266 Seiten, Format (B × H): 191 mm x 235 mm, Gewicht: 610 g

Reihe: Intelligent Data-Centric Syste

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.

Zielgruppe

<p>Researchers, graduate students, and professionals in the fields of computer science, systems engineering, telecommunication systems and smart cities technologies</p>

Autoren/Hrsg.

Al-Turjman, Fadi

Deebak, B.D.

Fachgebiete

• Medizin | Veterinärmedizin Medizin | Public Health | Pharmazie | Zahnmedizin Medizin, Gesundheitswesen Medizintechnik, Biomedizintechnik, Medizinische Werkstoffe
• Mathematik | Informatik EDV | Informatik Digital Lifestyle Soziale Netzwerke
• Medizin | Veterinärmedizin Medizin | Public Health | Pharmazie | Zahnmedizin Medizin, Gesundheitswesen Medizinische Mathematik & Informatik
• Technische Wissenschaften Sonstige Technologien | Angewandte Technik Medizintechnik, Biomedizintechnik

Inhaltsverzeichnis

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

Über Autor(innen)

Deebak, B.D.
B.D. Deebak is an associate professor in the Department of Computational Intelligence, School of Computer Science and Engineering at Vellore Institute of Technology, Vellore, India. Previously, he was at GMR Institute of Technology, Rajam as an associate professor in the Department of Computer Science and Engineering and before that in Middle East Technical University (METU) Northern Cyprus Campus. He has more than 12 years of teaching experience and research in various engineering institutions. His areas of research include multimedia networks, network security, and machine learning.