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Adversarial and Uncertain Reasoning for Adaptive Cyber Defense

Control- and Game-Theoretic Approaches to Cyber Security

  • Sushil Jajodia
  • George Cybenko
  • Peng Liu
  • Cliff Wang
  • Michael Wellman

Part of the Lecture Notes in Computer Science book series (LNCS, volume 11830)

Also part of the Security and Cryptology book sub series (LNSC, volume 11830)

Table of contents

  1. Front Matter
    Pages i-vii
  2. George Cybenko, Michael Wellman, Peng Liu, Minghui Zhu
    Pages 1-11
  3. Erik Miehling, Mohammad Rasouli, Demosthenis Teneketzis
    Pages 12-28
  4. Hamidreza Tavafoghi, Yi Ouyang, Demosthenis Teneketzis, Michael P. Wellman
    Pages 29-53
  5. Zhisheng Hu, Ping Chen, Minghui Zhu, Peng Liu
    Pages 54-93
  6. Massimiliano Albanese, Warren Connell, Sridhar Venkatesan, George Cybenko
    Pages 94-111
  7. Michael P. Wellman, Thanh H. Nguyen, Mason Wright
    Pages 112-128
  8. Ping Chen, Zhisheng Hu, Jun Xu, Minghui Zhu, Rob Erbacher, Sushil Jajodia et al.
    Pages 129-155
  9. Massimiliano Albanese, Sushil Jajodia, Sridhar Venkatesan, George Cybenko, Thanh Nguyen
    Pages 156-205
  10. Rajesh Ganesan, Ankit Shah, Sushil Jajodia, Hasan Cam
    Pages 206-231
  11. Benjamin W. Priest, George Cybenko, Satinder Singh, Massimiliano Albanese, Peng Liu
    Pages 232-261
  12. Back Matter
    Pages 263-263

About this book

Introduction

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 game theory to address the goal of computing effective strategies in dynamic, adversarial environments.

 

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

Editors and affiliations

  1. 1.George Mason UniversityFairfaxUSA
  2. 2.Dartmouth CollegeHanoverUSA
  3. 3.Pennsylvania State UniversityUniversity ParkUSA
  4. 4.Army Research LaboratoryTriangle ParkUSA
  5. 5.University of MichiganAnn ArborUSA

Bibliographic information

  • DOI https://doi.org/10.1007/978-3-030-30719-6
  • Copyright Information Springer Nature Switzerland AG 2019
  • Publisher Name Springer, Cham
  • eBook Packages Computer Science
  • Print ISBN 978-3-030-30718-9
  • Online ISBN 978-3-030-30719-6
  • Series Print ISSN 0302-9743
  • Series Online ISSN 1611-3349
  • Buy this book on publisher's site