{"product_id":"9781394206452","title":"Reinforcement Learning for Cyber Operations Applications of Artificial Intelligence for Penetration Testing","description":"\u003ch1\u003eReinforcement Learning for Cyber Operations\u003c\/h1\u003e\u003ch2\u003eApplications of Artificial Intelligence for Penetration Testing\u003c\/h2\u003e\u003ch3\u003eAbdul Rahman | Christopher Redino | Dhruv Nandakumar | Tyler Cody | Sachin Shetty | Dan Radke\u003c\/h3\u003e\u003cdiv\u003e\u003cb\u003eComputers \/ Artificial Intelligence \/ General\u003c\/b\u003e\u003c\/div\u003e\u003cbr\u003e\u003cdiv\u003e\n\u003cp\u003e\u003cb\u003eA comprehensive and up-to-date application of reinforcement learning concepts to offensive and defensive cybersecurity\u003c\/b\u003e \u003c\/p\u003e\n\u003cp\u003eIn \u003ci\u003eReinforcement Learning for Cyber Operations: Applications of Artificial Intelligence for Penetration Testing\u003c\/i\u003e, 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. \u003c\/p\u003e\n\u003cp\u003eContaining 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: \u003c\/p\u003e\n\u003cul\u003e\n\u003cli\u003eA thorough introduction to modeling actions within post-exploitation cybersecurity events, including Markov Decision Processes employing warm-up phases and penalty scaling\u003c\/li\u003e \u003cli\u003eComprehensive explorations of penetration testing automation, including how RL is trained and tested over a standard attack graph construct\u003c\/li\u003e \u003cli\u003ePractical discussions of both red and blue team objectives in their efforts to exploit and defend networks, respectively\u003c\/li\u003e \u003cli\u003eComplete treatment of how reinforcement learning can be applied to real-world cybersecurity operational scenarios\u003c\/li\u003e\n\u003c\/ul\u003e \u003cp\u003ePerfect for practitioners working in cybersecurity, including cyber defenders and planners, network administrators, and information security professionals, \u003ci\u003eReinforcement Learning for Cyber Operations: Applications of Artificial Intelligence for Penetration Testing\u003c\/i\u003e will also benefit computer science researchers.\u003c\/p\u003e\n\u003c\/div\u003e\u003cdiv\u003e  \u003cp\u003e\u003cb\u003eDr. Abdul Rahman\u003c\/b\u003e holds PhDs in physics, math, information technology–cybersecurity and has expertise in cybersecurity, big data, blockchain, and analytics (AI, ML). \u003c\/p\u003e\n\u003cp\u003e\u003cb\u003eDr. Christopher Redino\u003c\/b\u003e holds a PhD in theoretical physics and has extensive data science experience in every part of the AI \/ ML lifecycle. \u003c\/p\u003e\n\u003cp\u003e\u003cb\u003eMr. Dhruv Nandakumar\u003c\/b\u003e has extensive data science expertise in deep learning. \u003c\/p\u003e\n\u003cp\u003e\u003cb\u003eDr. Tyler Cody\u003c\/b\u003e is an Assistant Research Professor at the Virginia Tech National Security Institute. \u003c\/p\u003e\n\u003cp\u003e\u003cb\u003eDr. Sachin Shetty\u003c\/b\u003e is a Professor in the Electrical and Computer Engineering Department at Old Dominion University and the Executive Director of the Center for Secure and Intelligent Critical Systems at the Virginia Modeling, Analysis and Simulation Center. \u003c\/p\u003e\n\u003cp\u003e\u003cb\u003eMr. Dan Radke\u003c\/b\u003e is an Information Security professional with extensive experience in both offensive and defensive cybersecurity. \u003c\/p\u003e\n\u003c\/div\u003e\u003cbr\u003e\u003ctable\u003e\n\u003ctr\u003e\n\u003ctd\u003ePublication Date: \u003c\/td\u003e\n\u003ctd\u003e15 January 2025\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd\u003ePublisher: \u003c\/td\u003e\n\u003ctd\u003eWiley\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd\u003eImprint: \u003c\/td\u003e\n\u003ctd\u003eWiley-IEEE Press\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd\u003eISBN-13: \u003c\/td\u003e\n\u003ctd\u003e9781394206452\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd\u003eFormat: \u003c\/td\u003e\n\u003ctd\u003eHardback\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd\u003ePage Count: \u003c\/td\u003e\n\u003ctd\u003e288\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd\u003eWeight (oz): \u003c\/td\u003e\n\u003ctd\u003e23.36\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003c\/table\u003e","brand":"Wiley","offers":[{"title":"Default Title","offer_id":44380507373708,"sku":"9781394206452","price":125.06,"currency_code":"USD","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0710\/9545\/1788\/files\/9781394206452_14755ab6-cd79-4789-b414-2e68fd2d2f7d.jpg?v=1780102530","url":"https:\/\/fh90cf-fv.myshopify.com\/products\/9781394206452","provider":"Late Knight Books and Services, LLC","version":"1.0","type":"link"}