Decision and Game Theory for Security: 11th International Conference, GameSec 2020, College Park, MD, USA, October 28–30, 2020, Proceedings

Cognitive radio networks can be used to detect anomalous and adversarial communications to achieve situational awareness on the radio frequency spectrum. This paper proposes a distributed anomaly detection scheme based on adversarially-trained data models. While many anomaly detection methods typically depend on a central decisionmaking server, our distributed approach makes better use of decentralized resources, and decreases reliance on a single point of failure. Using a novel combination of generative adversarial network (GAN) elements, participating cognitive radio devices learn a representation of local network activity data through a non-cooperative (strategic) game. Deviations from this expected network activity are flagged as anomalies and treated as possible network security threats, improving situational awareness. Tested on a range of time series datasets, the performance of the proposed distributed scheme matches that of state-of-the-art, centralized anomaly detection methods.

[1]  Jie Fu,et al.  A Compositional Approach to Reactive Games under Temporal Logic Specifications , 2018, 2018 Annual American Control Conference (ACC).

[2]  Manish Jain,et al.  Computing optimal randomized resource allocations for massive security games , 2009, AAMAS.

[3]  Christel Baier,et al.  Principles of model checking , 2008 .

[4]  Eero P. Simoncelli,et al.  Image quality assessment: from error visibility to structural similarity , 2004, IEEE Transactions on Image Processing.

[5]  Wenruo Bai,et al.  Greed is Still Good: Maximizing Monotone Submodular+Supermodular Functions , 2018, ICML.

[6]  Kyoichi Kijima,et al.  Hierarchical hypergames and Bayesian games: A generalization of the theoretical comparison of hypergames and Bayesian games considering hierarchy of perceptions , 2016, J. Syst. Sci. Complex..

[7]  Vijay V. Vazirani,et al.  Approximation Algorithms , 2001, Springer Berlin Heidelberg.

[8]  Xinming Ou,et al.  A scalable approach to attack graph generation , 2006, CCS '06.

[9]  Roshan K. Thomas,et al.  Bridging the Classical D&D and Cyber Security Domains , 2015 .

[10]  Branislav Bosanský,et al.  Optimal Network Security Hardening Using Attack Graph Games , 2015, IJCAI.

[11]  Krishnendu Chatterjee,et al.  Graph Games and Reactive Synthesis , 2018, Handbook of Model Checking.

[12]  Viliam Lisý,et al.  Game-Theoretic Foundations for the Strategic Use of Honeypots in Network Security , 2015, Cyber Warfare.

[13]  Somesh Jha,et al.  Two formal analyses of attack graphs , 2002, Proceedings 15th IEEE Computer Security Foundations Workshop. CSFW-15.

[14]  Alan C. Bovik,et al.  Mean squared error: Love it or leave it? A new look at Signal Fidelity Measures , 2009, IEEE Signal Processing Magazine.

[15]  Weisi Lin,et al.  Just-noticeable difference estimation with pixels in images , 2008, J. Vis. Commun. Image Represent..

[16]  Haifeng Xu,et al.  Cyber Camouflage Games for Strategic Deception , 2019, GameSec.

[17]  Charles A. Kamhoua,et al.  Deceptive Labeling: Hypergames on Graphs for Stealthy Deception , 2021, IEEE Control Systems Letters.

[18]  Pan He,et al.  Adversarial Examples: Attacks and Defenses for Deep Learning , 2017, IEEE Transactions on Neural Networks and Learning Systems.

[19]  Bo An,et al.  Stackelberg Security Games: Looking Beyond a Decade of Success , 2018, IJCAI.

[20]  Branislav Bosanský,et al.  Game Theoretic Model of Strategic Honeypot Selection in Computer Networks , 2012, GameSec.

[21]  Jean-François Raskin,et al.  Antichains and compositional algorithms for LTL synthesis , 2011, Formal Methods Syst. Des..

[22]  U. Neisser.  VISUAL SEARCH. , 1964, Scientific American.

[23]  Zohar Manna,et al.  The Temporal Logic of Reactive and Concurrent Systems , 1991, Springer New York.

[24]  Thomas A. Henzinger,et al.  Concurrent reachability games , 2007, Theor. Comput. Sci..

[25]  Charles Kamhoua,et al.  Honeypot Allocation over Attack Graphs in Cyber Deception Games , 2020, 2020 International Conference on Computing, Networking and Communications (ICNC).

[26]  René Mazala,et al.  Infinite Games , 2001, Automata, Logics, and Infinite Games.

[27]  Robert McNaughton,et al.  Infinite Games Played on Finite Graphs , 1993, Ann. Pure Appl. Logic.

[28]  Peter Bennett,et al.  Hypergame Theory and Methodology: the Current “State of the Art” , 1986 .

[29]  Wei Jiang,et al.  Optimal Network Security Strengthening Using Attack-Defense Game Model , 2009, 2009 Sixth International Conference on Information Technology: New Generations.

[30]  Flemming Nielson,et al.  Quantitative Verification and Synthesis of Attack-Defence Scenarios , 2016, 2016 IEEE 29th Computer Security Foundations Symposium (CSF).