Game Theory and Machine Learning for Cyber Security

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Game Theory and Machine Learning for Cyber Security

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內容描述

This book describes a comprehensive suite of solutions to a broad range of technical issues in applying game theory and machine learning to solve cyber security challenges. It begins by introducing basic concepts on game theory, machine learning, cyber security and cyber deception. Further chapters bring together the best researchers and practitioners in cyber security to share their latest research contributions in hypergames, behavioral game theory, adversarial machine learning, generative adversarial networks, and multi-agent reinforcement learning. The book provides expert insights on applying these new methods to address cyber autonomy, 5G security, blockchain technology, attack graphs, sensor manipulation, fault injection, moving target defense, Cyber-Physical Systems (CPS), Internet-of-Battle- Things (IoBT), multi-domain battle. The book closes by summarizing ongoing research topics in cyber security and points to open issues and future research challenges.