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.



Inhalt

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

Titel
Deep Learning Techniques for IoT Security and Privacy
EAN
9783030890254
Format
E-Book (pdf)
Veröffentlichung
05.12.2021
Digitaler Kopierschutz
Wasserzeichen
Dateigrösse
6.47 MB
Anzahl Seiten
257