Security in IoT Social Networks

Security in IoT Social Networks
Author :
Publisher : Academic Press
Total Pages : 268
Release :
ISBN-10 : 9780128216033
ISBN-13 : 0128216034
Rating : 4/5 (33 Downloads)

Book Synopsis Security in IoT Social Networks by : Fadi Al-Turjman

Download or read book Security in IoT Social Networks written by Fadi Al-Turjman and published by Academic Press. This book was released on 2020-11-03 with total page 268 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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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