Mohamed Abdel-Basset, Nour Moustafa, Hossam Hawash, Weiping Ding

Deep Learning Techniques for IoT Security and Privacy (eBook, PDF)

• Format: PDF

Produktbeschreibung

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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Produktdetails

• Verlag: Springer International Publishing
• Seitenzahl: 257
• Erscheinungstermin: 5. Dezember 2021
• Englisch
• ISBN-13: 9783030890254
• Artikelnr.: 63097609

Inhaltsangabe

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.