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AI in modern computing systems transforms how hardware security is designed and defended. AI-driven hardware security utilizes machine learning and intelligent algorithms to detect threats, predict vulnerabilities, and respond to attacks at the hardware level. By enabling adaptive, real-time protection against sophisticated attacks, AI introduces a proactive security tactic that evolves with new threats. This convergence of AI and hardware security safeguards critical infrastructure, IoT devices, and next-generation computing platforms. AI-Driven Hardware Security: Architectures, Chips, and Trust explores how AI-driven technologies redefine chip design, semiconductor architecture, and trusted hardware systems in the modern computing era. It investigates both the opportunities and challenges arising from integrating AI into hardware verification, cryptographic module design, side-channel attack prevention, and system reliability. This book covers topics such as computer security, federated learning, and supply chains, and is a useful resource for computer engineers, security professionals, academicians, researchers, and scientists.
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