Computational adversarial risk analysis for general security games

TL;DR

This paper introduces a computational framework for security games using adversarial risk analysis, leveraging influence diagrams and simulation to handle complex scenarios, demonstrated through a disinformation war case study.

Contribution

It presents a novel computational scheme for general security games employing influence diagrams and augmented probability simulation, applicable to single and multi-stage scenarios.

Findings

Effective handling of complex security game scenarios

Theoretical convergence guarantees

Successful application to a disinformation war case study

Abstract

This paper provides an efficient computational scheme to handle general security games from an adversarial risk analysis perspective. Two cases in relation to single-stage and multi-stage simultaneous defend-attack games motivate our approach to general setups which uses bi-agent influence diagrams as underlying problem structure and augmented probability simulation as core computational methodology. Theoretical convergence and numerical, modeling, and implementation issues are thoroughly discussed. A disinformation war case study illustrates the relevance of the proposed approach.