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Modeling and Analysis of Deception Games Based on Hypergame Theory

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Autonomous Cyber Deception

Abstract

In this chapter, we discuss a deception game where attackers and defenders can have different perceptions towards a given situation. Although existing game theories have considered incomplete information to consider uncertainty, how players’ different perceptions or misperceptions can affect their decision-making has not been fully addressed. In particular, we discuss hypergame theory which has been used to resolve conflicts under uncertainty. In this chapter, we examine how a player’s perception (or misperception) affects their decision-making in choosing a best strategy based on hypergame theory. To deliver a concrete idea on how the attack–defense game can be modeled based on hypergame theory, we model a simple cybergame scenario and demonstrate an example probability model using Stochastic Petri Nets. Through the evaluation of the model, we show the experimental results to deliver insightful findings in terms of the relationships between perceptions by different players (i.e., an attacker or a defender), their chosen best strategies, and corresponding utilities. Lastly, we measure performance of the attacker and the defender in terms of attack success probability and mean time to security failure.

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Change history

  • 01 February 2020

    This book was inadvertently published as an authored work with the chapter authors mentioned in the footnotes of the chapter opening pages. This has now been updated and the chapter authors have been mentioned in the respective chapter opening pages as mentioned below:

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Correspondence to Jin-Hee Cho .

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Cho, JH., Zhu, M., Singh, M. (2019). Modeling and Analysis of Deception Games Based on Hypergame Theory. In: Al-Shaer, E., Wei, J., Hamlen, K., Wang, C. (eds) Autonomous Cyber Deception. Springer, Cham. https://doi.org/10.1007/978-3-030-02110-8_4

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  • DOI: https://doi.org/10.1007/978-3-030-02110-8_4

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-02109-2

  • Online ISBN: 978-3-030-02110-8

  • eBook Packages: Computer ScienceComputer Science (R0)

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