E-Books →Game Theory and Machine Learning for Cyber Security

Readers will explore the vulnerabilities of traditional machine learning algorithms and how they can be mitigated in an adversarial machine learning approach.The book offers a comprehensive suite of solutions to a broad range of technical issues in applying game theory and machine learning to solve cyber security challenges.
Beginning with an introduction to foundational concepts in game theory, machine learning, cyber security, and cyber deception, the editorsprovide readers with resources that discuss the latest in hypergames, behavioral game theory, adversarial machine learning, generative adversarial networks, and multi-agent reinforcement learning.
Readers will also enjoy:

• A thorough introduction to game theory for cyber deception, including scalable algorithms for identifying stealthy attackers in a game theoretic framework, honeypot allocation over attack graphs, and behavioral games for cyber deception
  
• An exploration of game theory for cyber security, including actionable game-theoretic adversarial intervention detection against persistent and advanced threats
  
• Practical discussionsof adversarial machine learning for cyber security, including adversarial machine learning in 5G securityand machine learning-driven fault injection in cyber-physical systems
  
• In-depth examinations of generative models for cyber security
  

Perfect for researchers, students, and experts in the fields of computer science and engineering,Game Theory and Machine Learning for Cyber Securityis also an indispensable resource for industry professionals, military personnel, researchers, faculty, and students with an interest in cyber security.