Bộ sách luyện thi ETS 2023 LC&RC
199,000₫
299,000₫
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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.
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.
You’ll also find:
A thorough
introduction to modeling actions within post-exploitation cybersecurity
events, including Markov Decision Processes employing warm-up phases and
penalty scaling
Comprehensive explorations of penetration
testing automation, including how RL is trained and tested over a
standard attack graph construct
Practical discussions of both red and blue team objectives in their efforts to exploit and defend networks, respectively
Complete treatment of how reinforcement learning can be applied to real-world cybersecurity operational scenarios
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.
Categories:Computers - Artificial Intelligence (AI)
Content Type:Books
Year:2025
Language:english
Pages:277
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