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.
Rajat Subhra Chakraborty & Pranesh Santikellur
Deep Learning for Computational Problems in Hardware Security [EPUB ebook]
Modeling Attacks on Strong Physically Unclonable Function Circuits
Deep Learning for Computational Problems in Hardware Security [EPUB ebook]
Modeling Attacks on Strong Physically Unclonable Function Circuits
Mua cuốn sách điện tử này và nhận thêm 1 cuốn MIỄN PHÍ!
Ngôn ngữ Anh ● định dạng EPUB ● ISBN 9789811940170 ● Nhà xuất bản Springer Nature Singapore ● Được phát hành 2022 ● Có thể tải xuống 3 lần ● Tiền tệ EUR ● TÔI 8643753 ● Sao chép bảo vệ Adobe DRM
Yêu cầu trình đọc ebook có khả năng DRM