Abstract
We seek to combine recent advances in game theory of both cyber defense and deception to model the interactions between an attacker and defender on a network. We define a new class of games called \((n,k,c,{\varvec{w}}, \gamma )\)-honeynet games which extend those defined in previous research. These games have incomplete and imperfect information since the attacker is unaware of moves made by the defender to secure a system, and the defender is not certain of the true identity of the attacker.
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Notes
- 1.
The domain of \(p_N^*\) is \(\varDelta _{K_E}\coprod \varDelta _0\), where \(\varDelta _0\) is just the point \(\{1\}\) representing the friendly node’s unique strategy.
References
Carroll, T.E., Grosu, D.: A game theoretic investigation of deception in network security. In: 2009 Proceedings of 18th International Conference on Computer Communications and Networks - ICCCN 2009, pp. 1–6. IEEE (2009)
Dutt, V., Ahn, Y.S., Gonzalez, C.: Cyber situation awareness: modeling detection of cyber attacks with instance-based learning theory. Hum. Factors 55(3), 605–618 (2013). https://doi.org/10.1177/0018720812464045
Garg, N., Grosu, D.: Deception in HoneyNets: a game-theoretic analysis. In: 2007 IEEE SMC Information Assurance and Security Workshop, pp. 107–113. IEEE (2007)
Gonzalez, C., Dutt, V.: Instance-based learning: integrating sampling and repeated decisions from experience. Psychol. Rev. 118(4), 523 (2011)
Kahneman, D., Tversky, A.: Prospect theory: an analysis of decision under risk, pp. 99–127. World Scientific (2013). chap. 6. https://doi.org/10.1142/9789814417358_0006
Liu, Y., Comaniciu, C., Man, H.: A Bayesian game approach for intrusion detection in wireless ad hoc networks. In: Proceedings from the 2006 Workshop, p. 4. ACM Press, New York (2006)
Píbil, R., Lisý, V., Kiekintveld, C., Bošanský, B., Pěchouček, M.: Game theoretic model of strategic honeypot selection in computer networks. In: Grossklags, J., Walrand, J. (eds.) GameSec 2012. LNCS, vol. 7638, pp. 201–220. Springer, Heidelberg (2012). https://doi.org/10.1007/978-3-642-34266-0_12
Rowe, N.C., Custy, E.J.: Deception in cyber-attacks (2007). https://calhoun.nps.edu/handle/10945/36422
Acknowledgements
We thank Kimberly Ferguson-Walter and Dr. Sunny Fugate for their technical direction and the reviewers for their helpful comments.
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© 2018 This is a U.S. government work and not under copyright protection in the U.S.; foreign copyright protection may apply 2018
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Bilinski, M., Gabrys, R., Mauger, J. (2018). Optimal Placement of Honeypots for Network Defense. In: Bushnell, L., Poovendran, R., Başar, T. (eds) Decision and Game Theory for Security. GameSec 2018. Lecture Notes in Computer Science(), vol 11199. Springer, Cham. https://doi.org/10.1007/978-3-030-01554-1_7
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DOI: https://doi.org/10.1007/978-3-030-01554-1_7
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