Könyv Deep Learning for Computational Problems in Hardware Security Pranesh Santikellur

Deep Learning for Computational Problems in Hardware Security

Modeling Attacks on Strong Physically Unclonable Function Circuits

Nyelv: Angol
Kötés: Kemény kötésű
Elérhetőség: Beszállítói készleten
Küldés 10-18 napon belül
22 781 Ft
The book discusses a broad overview of traditional machine learning methods and state-of-the-art dee...

Információk a könyvről

Nyelv
Angol
Kötés
Könyv - Kemény kötésű
Kiadva
2022
oldal
84
EAN
9789811940163
Enbook ID
39239432
Súly
325
Méretek
155 x 235 x 12

Teljes leírás

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.

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