Название: Reinforcement Learning for Cyber Operations: Applications of Artificial Intelligence for Penetration Testing
Автор: Abdul Rahman, Christopher Redino, Dhruv Nandakumar, Tyler Cody, Sachin Shetty, Dan Radke
Издательство: Wiley-IEEE Press
Год: 2025
Страниц: 277
Язык: английский
Формат: pdf (true), epub
Размер: 10.1 MB
A comprehensive and up-to-date application of Reinforcement Learning concepts to offensive and defensive cybersecurity. In Reinforcement Learning for Cyber Operations: Applications of Artificial Intelligence for Penetration Testing, a team of distinguished researchers delivers an incisive and practical discussion of Reinforcement Learning (RL) in cybersecurity that combines intelligence preparation for battle (IPB) concepts with multi-agent techniques. The authors explain how to conduct path analyses within networks, how to use sensor placement to increase the visibility of adversarial tactics and increase cyber defender efficacy, and how to improve your organization’s cyber posture with RL and illuminate the most probable adversarial attack paths in your networks. Perfect for practitioners working in cybersecurity, including cyber defenders and planners, network administrators, and information security professionals, Reinforcement Learning for Cyber Operations: Applications of Artificial Intelligence for Penetration Testing will also benefit Computer Science researchers.
