Reinforcement Learning for Cyber Operations: Applications of Artificial Intelligence for Penetration
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Description
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.
Containing entirely original research, this book outlines findings and real-world scenarios that have been modeled and tested against custom generated networks, simulated networks, and data. [Amazon.com]
ISBN
9781394206476
DOI
10.1002/9781394206483
Publication Date
1-2025
Publisher
John Wiley & Sons, Incorporated
City
Newark, NJ
Disciplines
Artificial Intelligence and Robotics | Cybersecurity
Recommended Citation
Rahman, Abdul; Redino, Christopher; Nandakumar, Dhruv; Cody, Tyler; Shetty, Sachhin; and Radke, Dan, "Reinforcement Learning for Cyber Operations: Applications of Artificial Intelligence for Penetration" (2025). Electrical & Computer Engineering Faculty Books. 13.
https://digitalcommons.odu.edu/ece_books/13