Adaptive Autonomous Secure Cyber Systems, 1st ed. 2020
Langue : Anglais
Coordonnateurs : Jajodia Sushil, Cybenko George, Subrahmanian V.S., Swarup Vipin, Wang Cliff, Wellman Michael
This book explores fundamental scientific problems essential for autonomous cyber defense. Specific areas include:
- Game and control theory-based moving target defenses (MTDs) and adaptive cyber defenses (ACDs) for fully autonomous cyber operations;
- The extent to which autonomous cyber systems can be designed and operated in a framework that is significantly different from the human-based systems we now operate;
- On-line learning algorithms, including deep recurrent networks and reinforcement learning, for the kinds of situation awareness and decisions that autonomous cyber systems will require;
- Human understanding and control of highly distributed autonomous cyber defenses;
- Quantitative performance metrics for the above so that autonomous cyber defensive agents can reason about the situation and appropriate responses as well as allowing humans to assess and improve the autonomous system.
This book establishes scientific foundations for adaptive autonomous cyber systems and ultimately brings about a more secure and reliable Internet. The recent advances in adaptive cyber defense (ACD) have developed a range of new ACD techniques and methodologies for reasoning in an adaptive environment.
Autonomy in physical and cyber systems promises to revolutionize cyber operations. The ability of autonomous systems to execute at scales, scopes, and tempos exceeding those of humans and human-controlled systems will introduce entirely new types of cyber defense strategies and tactics, especially in highly contested physical and cyber environments. The development and automation of cyber strategies that are responsive to autonomous adversaries pose basic new technical challenges for cyber-security.
This book targets cyber-security professionals and researchers (industry, governments, and military). Advanced-level students in computer science and information systems will also find this book useful as a secondary textbook.
1. Reference Architecture of an Autonomous Agent for Cyber Defense of Complex Military Systems.- 2. Defending against Machine Learning based Inference Attacks via Adversarial Examples: Opportunities and Challenges.- 3. Exploring Adversarial Artificial Intelligence for Autonomous Adaptive Cyber Defense.- 4. Can Cyber Operations be Made Autonomous? An Answer from the Situational Awareness Viewpoint.- 5. A framework for studying autonomic computing models in cyber deception.- 6. Autonomous Security Mechanisms for High-Performance Computing Systems: Review and Analysis.- 7. Automated Cyber Risk Mitigation: Making Informed Cost-effective Decisions.- 8. Plan Interdiction Games.- 9. Game Theoretic Cyber Deception to Foil Adversarial Network Reconnaissance.- 10. Strategic Learning for Active, Adaptive, and Autonomous Cyber Defense.- 11. Online Learning Methods for Controlling Dynamic Cyber Deception Strategies.- 12. Phishing URL Detection with Lexical Features and Blacklisted Domains.- 13. An Empirical Study of Secret Security Patch in Open Source Software.
Sushil Jajodia is University Professor, BDM International Professor, and the founding director of Center for Secure Information Systems in the Volgenau School of Engineering at the George Mason University, Fairfax, Virginia. His research interests include security, privacy, databases, and distributed systems. He has authored or coauthored seven books, edited 43 books and conference proceedings, and published more than 450 technical papers in the refereed journals and conference proceedings. He is also a holder of seventeen patents.
George Cybenko is the Dorothy and Walter Gramm Professor of Engineering at Dartmouth. Professor Cybenko has made key research contributions in signal processing, neural computing, parallel processing and computational behavioral analysis. He was the Founding Editor-in-Chief of IEEE/AIP Computing in Science and Engineering and IEEE Security & Privacy. Professor Cybenko is a Fellow of the IEEE and received his BS (University of Toronto) and PhD (Princeton) degrees in Mathematics.
V.S. Subrahmanian is The Dartmouth College Distinguished Professor in Cybersecurity, Technology, and Society at Dartmouth College. Prof. Subrahmanian is one of the world leaders in logical reasoning with uncertainty, probabilistic logics, temporal probabilistic logics, and managing huge, heterogeneous databases with incomplete and inconsistent information, and multimedia databases. He serves on the boards of numerous journals including Science, ACM Transactions on Intelligent Systems & Technology, ACM Transactions on Computational Logic, and IEEE Transactions on Computational Social Systems.
Vipin Swarup is director of the Cyber Resilient Systems at the MITRE Corporation, McLean, VA. He is the recipient of MITRE’s first Technology Transfer Individual Contribution Award for entrepreneurial leadership and success in transferring MITRE innovat
Presents the latest research on the attribution problem to help identify culprits of cyber-attacks
Describes how a variety of subfields of computer science are applied to cyber-security including artificial intelligence, game theory, programming languages, and graph theory
Features chapters by leading scientists in the cyber-security field
Date de parution : 02-2021
Ouvrage de 289 p.
15.5x23.5 cm
Date de parution : 02-2020
Ouvrage de 289 p.
15.5x23.5 cm
Thème d’Adaptive Autonomous Secure Cyber Systems :
Mots-clés :
Cyber security; adaptive cyber defense; cyber attacks; cyber defense; network security; autonomous systems; science of security; game theory; Autonomic computing; Cyber deception; machine learning; programming languages; graph theory; Adversarial artificial intelligence; Generative adversarial networks; Quantitative performance metrics; Deep learning
© 2024 LAVOISIER S.A.S.
Ces ouvrages sont susceptibles de vous intéresser
Cyber Security: Power and Technology 116,04 €