Deep Learning for Computational Problems in Hardware Security : Modeling ...
Springer Verlag, Singapore
Explore cutting-edge advancements in hardware security with "Deep Learning for Computational Problems in Hardware Security." This book delves into sophisticated modeling techniques for attacks on Physically Unclonable Function (PUF) circuits, offering crucial insights for researchers and professionals in the field. Authored by Pranesh Santikellur, it provides a comprehensive analysis of deep learning applications in identifying and mitigating security vulnerabilities within hardware systems. Key Features: * In-depth exploration of deep learning models for hardware security. * Detailed analysis of attacks targeting Physically Unclonable Function circuits. * Practical modeling approaches for identifying vulnerabilities. * Essential reading for cybersecurity experts and researchers. This hardback edition presents a thorough examination of current challenges and innovative solutions in hardware security, making it an invaluable resource for anyone involved in protecting sensitive digital infrastructure.
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