Machine Learning for Embedded System Security Paperback / softback
Edited by Basel Halak
Paperback / softback
- Information
Description
This book comprehensively covers the state-of-the-art security applications of machine learning techniques. The first part explains the emerging solutions for anti-tamper design, IC Counterfeits detection and hardware Trojan identification.
It also explains the latest development of deep-learning-based modeling attacks on physically unclonable functions and outlines the design principles of more resilient PUF architectures.
The second discusses the use of machine learning to mitigate the risks of security attacks on cyber-physical systems, with a particular focus on power plants.
The third part provides an in-depth insight into the principles of malware analysis in embedded systems and describes how the usage of supervised learning techniques provides an effective approach to tackle software vulnerabilities.
Information
-
Available to Order - This title is available to order, with delivery expected within 2 weeks
- Format:Paperback / softback
- Pages:160 pages, 39 Illustrations, color; 27 Illustrations, black and white; XV, 160 p. 66 illus., 39 illu
- Publisher:Springer Nature Switzerland AG
- Publication Date:23/04/2023
- Category:
- ISBN:9783030941802
Information
-
Available to Order - This title is available to order, with delivery expected within 2 weeks
- Format:Paperback / softback
- Pages:160 pages, 39 Illustrations, color; 27 Illustrations, black and white; XV, 160 p. 66 illus., 39 illu
- Publisher:Springer Nature Switzerland AG
- Publication Date:23/04/2023
- Category:
- ISBN:9783030941802