Login

Fang, Fei

Game Theory and Machine Learning for Cyber Security

Fang, Fei - Game Theory and Machine Learning for Cyber Security, ebook

131,65€

Ebook, PDF with Adobe DRM
ISBN: 9781119723912
DRM Restrictions

Printing163 pages with an additional page accrued every 5 hours, capped at 163 pages
Copy to clipboard5 excerpts

Move beyond the foundations of machine learning and game theory in cyber security to the latest researchin this cutting-edge field

InGame Theory and Machine Learning for Cyber Security,a team of expert security researchers delivers acollection of central research contributions from both machine learning and game theoryapplicable to cybersecurity. The distinguished editors have included resources that address open research questions in game theory and machine learning applied to cyber security systems and examinethe strengths and limitations of current game theoretic models 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.

Keywords:

hypergames; behavioral game theory; adversarial machine learning; generative adversarial networks; multi-agent reinforcement learning; cyber autonomy; cyber deception; 5g security; blockchain security; attack graphs; fault injection 

, Communication System Security, Networking / Security, Computer Security & Cryptography, Communication System Security, Networking / Security, Computer Security & Cryptography
Editor
 
 
 
Publisher
John Wiley and Sons, Inc.
Publication year
2021
Language
en
Edition
1
Page amount
544 pages
Category
Technology, Energy, Traffic
Format
Ebook
eISBN (PDF)
9781119723912
Printed ISBN
9781119723929

Similar titles