1. Proceedings
  2. I3M
  3. 2022
  4. DHSS
  5. 10.46354/i3m.2022.dhss.002

Augmented probability simulation for adversarial risk analysis in general security games

  • a Roi Naveiro  ,
  • b avid Rios Insua, 
  • c Jose Manuel Camacho
  • a,b,c  Institute of Mathematical Sciences (ICMAT-CSIC), C/ Nicolás Cabrera 13-15, Madrid, 28049, Spain
Cite as
Naveiro R., Insua D.R., and Camacho J.M. (2022).,Augmented probability simulation for adversarial risk analysis in general security games. Proceedings of the 12th International Defense and Homeland Security Simulation Workshop (DHSS 2022). , 002 . DOI: https://doi.org/10.46354/i3m.2022.dhss.002
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Abstract

Although widely used, standard game-theoretic approaches to security games face severe shortcomings, being the common knowledge assumption a critical one. Adversarial Risk Analysis (ARA) is an alternative modeling framework that mitigates such limitations.
However, from a computational perspective, ARA is much more involved than its game theoretical counterparts. We propose an approach for finding ARA solutions to security games represented as bi-agent influence diagrams that is based on augmented probability simulation. We motivate this approach using two simple cases: sequential and simultaneous defend-attack models. We next provide the general framework and illustrate it in handling risks in a cybersecurity setting.

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