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Deep learning approaches for security threats in IoT environments /

by Abdel-Basset, Mohamed,
Authors: Moustafa, Nour,%author | Hawash, Hossam,%author | Ohio Library and Information Network. Published by : John Wiley & Sons, Inc., (Hoboken, New Jersey :) Physical details: xvi, 368 p. : ill. ; 23 cm. ISBN: 1119884144 Subject(s): Internet of things %Security measures %Data processing. | Deep learning (Machine learning) | Electronic books Year: 2023
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Item type Location Call Number Status Notes Date Due
Book Book AUM Main Library 004.678 A135 (Browse Shelf) Available inv 202301028

Includes bibliographical references and index

Available to OhioLINK libraries

"Deep Learning Approaches for Security Threats in IoT Environments discusses approaches and measures to ensure our IoT systems are secure. This book discusses important concepts of AI and IoT and applies vital approaches that can be used to protect our systems - these include supervised, unsupervised, and semi-supervised Deep Learning approaches as well as Reinforcement and Federated Learning for privacy-preserving. This book applies Digital Forensics to IoT and discusses problems that professionals may encounter when working in the field of IoT forensics, providing ways in which smart devices can solve cyber security issues. Aimed at readers within the cyber security field, this book presents the most recent challenges that are faced in deep learning when creating a secure platform for IoT systems and addresses the possible solutions, paving the way for a more secure future"--

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