Deep learning approaches for security threats in IoT environments
"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, unsupe...
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| Weitere Verfasser: | , |
| Format: | UnknownFormat |
| Sprache: | eng |
| Veröffentlicht: |
Piscataway, NJ
IEEE Press
2023
Hoboken, New Jersey Wiley 2023 |
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| Online Zugang: | Inhaltsverzeichnis |
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Tag hinzufügen | Zusammenfassung: | "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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| Beschreibung: | Includes bibliographical references and index |
| Beschreibung: | xvi, 368 Seiten Illustrationen, Diagramme |
| ISBN: | 9781119884149 978-1-119-88414-9 |