Deep Learning Techniques for IoT Security and Privacy

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ISBN-13:
9783030890247
Veröffentl:
2021
Einband:
HC runder Rücken kaschiert
Erscheinungsdatum:
06.12.2021
Seiten:
280
Autor:
Mohamed Abdel-Basset
Gewicht:
588 g
Format:
241x160x21 mm
Serie:
997, Studies in Computational Intelligence
Sprache:
Englisch
Beschreibung:

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.
Presents a Machine Learning Approach to Conducting Digital Forensics
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.

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