Overview
- Presents a new class of technologies that help prevent cyber attacks
- Features research by international experts
- Synthesizes recent advances
Part of the book series: Lecture Notes in Computer Science (LNCS, volume 11830)
Part of the book sub series: Security and Cryptology (LNSC)
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Table of contents (10 chapters)
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Front Matter
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Back Matter
Keywords
- adaptive cyber defense
- artificial intelligence
- botnets
- clustering
- computer operating systems
- control theory
- cryptography
- cyber security
- data management
- data mining
- data security
- game theory
- information technology
- malware
- moving targets
- nash equilibrium
- security systems
- sensors
- target tracking
- uncertain reasoning
About this book
Today’s cyber defenses are largely static allowing adversaries to pre-plan their attacks. In response to this situation, researchers have started to investigate various methods that make networked information systems less homogeneous and less predictable by engineering systems that have homogeneous functionalities but randomized manifestations.
The 10 papers included in this State-of-the Art Survey present recent advances made by a large team of researchers working on the same US Department of Defense Multidisciplinary University Research Initiative (MURI) project during 2013-2019. This project has developed a new class of technologies called Adaptive Cyber Defense (ACD) by building on two active but heretofore separate research areas: Adaptation Techniques (AT) and Adversarial Reasoning (AR). AT methods introduce diversity and uncertainty into networks, applications, and hosts. AR combines machine learning, behavioral science, operations research, control theory, and gametheory to address the goal of computing effective strategies in dynamic, adversarial environments.
Editors and Affiliations
Bibliographic Information
Book Title: Adversarial and Uncertain Reasoning for Adaptive Cyber Defense
Book Subtitle: Control- and Game-Theoretic Approaches to Cyber Security
Editors: Sushil Jajodia, George Cybenko, Peng Liu, Cliff Wang, Michael Wellman
Series Title: Lecture Notes in Computer Science
DOI: https://doi.org/10.1007/978-3-030-30719-6
Publisher: Springer Cham
eBook Packages: Computer Science, Computer Science (R0)
Copyright Information: Springer Nature Switzerland AG 2019
Softcover ISBN: 978-3-030-30718-9Published: 02 September 2019
eBook ISBN: 978-3-030-30719-6Published: 30 August 2019
Series ISSN: 0302-9743
Series E-ISSN: 1611-3349
Edition Number: 1
Number of Pages: VII, 263
Number of Illustrations: 75 b/w illustrations, 45 illustrations in colour
Topics: Computer Crime, Computer Systems Organization and Communication Networks, Computing Milieux, Information Systems and Communication Service, Probability and Statistics in Computer Science