Deep Learning for Computational Problems in Hardware Security

Language: English

Published by Springer Verlag, Singapore, SG, 2022

9811940169 / 9789811940163

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The book discusses a broad overview of traditional machine learning methods and state-of-the-art deep learning practices for hardware security applications, in particular the techniques of launching potent "modeling attacks" on Physically Unclonable Function (PUF) circuits, which are promising hardware security primitives. The volume is self-contained and includes a comprehensive background on PUF circuits, and the necessary mathematical foundation of traditional and advanced machine learning techniques such as support vector machines, logistic regression, neural networks, and deep learning. This book can be used as a self-learning resource for researchers and practitioners of hardware security, and will also be suitable for graduate-level courses on hardware security and application of machine learning in hardware security. A stand-out feature of the book is the availability of reference software code and datasets to replicate the experiments described in the book.

Seller Inventory # LU-9789811940163

Title
Deep Learning for Computational Problems in Hardware Security
Author
Pranesh Santikellur, Rajat Subhra Chakraborty
Publisher
Springer Verlag, Singapore, SG
Publication year
2022
Condition
New
Binding
Hardback
Language
English
ISBN 10
9811940169
ISBN 13
9789811940163
Edition
2023 ed.

Rarewaves.com UK

London, United Kingdom

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