Deep Learning for Computational Problems in Hardware Security: Modeling Attacks on Strong Physically Unclonable Function Circuits

Deep Learning for Computational Problems in Hardware Security: Modeling Attacks on Strong Physically Unclonable Function Circuits 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. Autor: Pranesh Santikellur, Rajat Subhra Chakraborty Wydawnictwo: Springer Rok wydania: 2022 Okładka: twarda Liczba stron: 84 Wymiary: 16.3 x 24.2 x 1.2 cm Ilustracje: 18 Illustrations, color; 13 Illustrations, black and white; XIII, 84 p. 31 illus., 18 illus. in color. Język: angielski ISBN: 9789811940163