| Description |
1 online resource (273 pages) |
| Series |
Studies in Computational Intelligence ; v. 997 |
|
Studies in computational intelligence ; v. 997.
|
| 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 |
| Bibliography |
Includes bibliographical references |
| Subject |
Machine learning.
|
|
Internet of things -- Security measures
|
|
Machine learning
|
| Form |
Electronic book
|
| Author |
Moustafa, Nour.
|
|
Hawash, Hossam
|
|
Ding, Weiping
|
| ISBN |
9783030890254 |
|
3030890252 |
|
