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Deep Learning Techniques for IoT Security and Privacy / by Mohamed Abdel-Basset, Nour Moustafa, Hossam Hawash, Weiping Ding

By: Abdel-Basset, Mohamed,, (1985-), autor
Contributor(s): Moustafa, Nour, autor | Hawash, Hossam, autor
Material type: materialTypeLabelE-bookSeries: (Studies in Computational Intelligence, 1860-9503 ; 997).Publisher: Cham : Springer International Publishing, 2022Edition: 1st edition 2022.Description: 1 recurso en línea (XXI, 257 páginas) : 71 ilustraciones, 69 ilustraciones a color.ISBN: 9783030890254.Subject: Aprendizaje automático | Internet de los objetosOnline resources: Acceso a este recurso digital (usuarios Universidad Europea de Madrid)Digital Resources
Contents:
Chapter 1, Conceptualization of Security, Forensics, and Privacy of Internet of Things -- Chapter 2, Internet of Things, Preliminaries and Foundations -- Chapter 3, Internet of Things Security Requirements, Threats, Countermeasures -- Chapter 4, Digital Forensics in Internet of Things -- Chapter 5, Supervised Deep Learning for Secure Internet of Things -- Chapter 6, Unsupervised Deep Learning for Secure Internet of Things -- Chapter 7, Semi-supervised Deep Learning for Secure Internet of Things -- Chapter 8, Reinforcement Learning for Secure Internet of Things -- Chapter 9, Federated Learning for Privacy-Preserving Internet of Things -- Chapter 10, Challenges, Opportunities, and Future Prospects.
Summary: This book states that the major aim audience are people who have some familiarity with Internet of things (IoT) but interested to get a comprehensive interpretation of the role of deep Learning in maintaining the security and privacy of IoT. A reader should be friendly with Python and the basics of machine learning and deep learning. Interpretation of statistics and probability theory will be a plus but is not certainly vital for identifying most of the book's material.
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Holdings
Item type Current library Collection Call number Status Date due Barcode Item holds
LIBRO-E NO PRÉSTAMO LIBRO-E NO PRÉSTAMO Madrid Digital Acceso Electrónico (UEM) Ciencias e Ingeniería Q325.5 2022 EB (Browse shelf(Opens below)) Acceso electrónico eBook.09012857
Total holds: 0

Chapter 1, Conceptualization of Security, Forensics, and Privacy of Internet of Things -- Chapter 2, Internet of Things, Preliminaries and Foundations -- Chapter 3, Internet of Things Security Requirements, Threats, Countermeasures -- Chapter 4, Digital Forensics in Internet of Things -- Chapter 5, Supervised Deep Learning for Secure Internet of Things -- Chapter 6, Unsupervised Deep Learning for Secure Internet of Things -- Chapter 7, Semi-supervised Deep Learning for Secure Internet of Things -- Chapter 8, Reinforcement Learning for Secure Internet of Things -- Chapter 9, Federated Learning for Privacy-Preserving Internet of Things -- Chapter 10, Challenges, Opportunities, and Future Prospects.

This book states that the major aim audience are people who have some familiarity with Internet of things (IoT) but interested to get a comprehensive interpretation of the role of deep Learning in maintaining the security and privacy of IoT. A reader should be friendly with Python and the basics of machine learning and deep learning. Interpretation of statistics and probability theory will be a plus but is not certainly vital for identifying most of the book's material.

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