Deep Learning for Computational Problems in Hardware Security

Modeling Attacks on Strong Physically Unclonable Function Circuits

By: Pranesh Santikellur, Rajat Subhra Chakraborty

Write A Review

Hardcover | 16 September 2022

At a Glance

Hardcover
100 Pages

Dimensions(cm)
16.3 x 24.2 x 1.2

Hardcover

RRP $169.00

$144.75

14%OFF

or 4 interest-free payments of $36.19 with

Ships in 10 to 15 business days

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.

Shipping

	Standard Shipping	Express Shipping
Metro postcodes:	$9.99	$14.95
Regional postcodes:	$9.99	$14.95
Rural postcodes:	$9.99	$14.95

Orders over $79.00 qualify for free shipping.

How to return your order

At Booktopia, we offer hassle-free returns in accordance with our returns policy. If you wish to return an item, please get in touch with Booktopia Customer Care.

Additional postage charges may be applicable.