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

Deep Learning Techniques for IoT Security and Privacy

Buch | Hardcover
XXI, 257 Seiten
2021
Springer International Publishing (Verlag)
978-3-030-89024-7 (ISBN)
CHF 239,65 inkl. MwSt
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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.

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.

Erscheinungsdatum
Reihe/Serie Studies in Computational Intelligence
Zusatzinfo XXI, 257 p. 71 illus., 69 illus. in color.
Verlagsort Cham
Sprache englisch
Maße 155 x 235 mm
Gewicht 577 g
Themenwelt Mathematik / Informatik Informatik Datenbanken
Informatik Theorie / Studium Künstliche Intelligenz / Robotik
Technik
Schlagworte cyber forensics • Digital Forensic Education • digital forensics • Social Media Forensics • Virtual Machines Forensics
ISBN-10 3-030-89024-4 / 3030890244
ISBN-13 978-3-030-89024-7 / 9783030890247
Zustand Neuware
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