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Adversarial Risk Analysis for Counterterrorism Modeling

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  • Jesus Rios
  • David Rios Insua

Abstract

Recent large‐scale terrorist attacks have raised interest in models for resource allocation against terrorist threats. The unifying theme in this area is the need to develop methods for the analysis of allocation decisions when risks stem from the intentional actions of intelligent adversaries. Most approaches to these problems have a game‐theoretic flavor although there are also several interesting decision‐analytic‐based proposals. One of them is the recently introduced framework for adversarial risk analysis, which deals with decision‐making problems that involve intelligent opponents and uncertain outcomes. We explore how adversarial risk analysis addresses some standard counterterrorism models: simultaneous defend‐attack models, sequential defend‐attack‐defend models, and sequential defend‐attack models with private information. For each model, we first assess critically what would be a typical game‐theoretic approach and then provide the corresponding solution proposed by the adversarial risk analysis framework, emphasizing how to coherently assess a predictive probability model of the adversary’s actions, in a context in which we aim at supporting decisions of a defender versus an attacker. This illustrates the application of adversarial risk analysis to basic counterterrorism models that may be used as basic building blocks for more complex risk analysis of counterterrorism problems.

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  • Jesus Rios & David Rios Insua, 2012. "Adversarial Risk Analysis for Counterterrorism Modeling," Risk Analysis, John Wiley & Sons, vol. 32(5), pages 894-915, May.
  • Handle: RePEc:wly:riskan:v:32:y:2012:i:5:p:894-915
    DOI: 10.1111/j.1539-6924.2011.01713.x
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    7. Mathews, Timothy & Paul, Jomon A., 2022. "Natural disasters and their impact on cooperation against a common enemy," European Journal of Operational Research, Elsevier, vol. 303(3), pages 1417-1428.
    8. Michael Macgregor Perry & Hadi El-Amine, 2021. "Computational Efficiency in Multivariate Adversarial Risk Analysis Models," Papers 2110.12572, arXiv.org.
    9. Vineet M. Payyappalli & Jun Zhuang & Victor Richmond R. Jose, 2017. "Deterrence and Risk Preferences in Sequential Attacker–Defender Games with Continuous Efforts," Risk Analysis, John Wiley & Sons, vol. 37(11), pages 2229-2245, November.
    10. Gregory F. Nemet & Laura Diaz Anadon & Elena Verdolini, 2017. "Quantifying the Effects of Expert Selection and Elicitation Design on Experts’ Confidence in Their Judgments About Future Energy Technologies," Risk Analysis, John Wiley & Sons, vol. 37(2), pages 315-330, February.
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    13. Wu, Di & Yan, Xiangbin & Peng, Rui & Wu, Shaomin, 2020. "Risk-attitude-based defense strategy considering proactive strike, preventive strike and imperfect false targets," Reliability Engineering and System Safety, Elsevier, vol. 196(C).
    14. William M. Kroshl & Shahram Sarkani & Thomas A Mazzuchi, 2015. "Efficient Allocation of Resources for Defense of Spatially Distributed Networks Using Agent‐Based Simulation," Risk Analysis, John Wiley & Sons, vol. 35(9), pages 1690-1705, September.
    15. Roponen, Juho & Ríos Insua, David & Salo, Ahti, 2020. "Adversarial risk analysis under partial information," European Journal of Operational Research, Elsevier, vol. 287(1), pages 306-316.
    16. Deng, Yu-Jing & Li, Ya-Qian & Qin, Yu-Hua & Dong, Ming-Ru & Liu, Bin, 2020. "Optimal defense resource allocation for attacks in wireless sensor networks based on risk assessment model," Chaos, Solitons & Fractals, Elsevier, vol. 137(C).
    17. Gilberto Montibeller & L. Alberto Franco & Ashley Carreras, 2020. "A Risk Analysis Framework for Prioritizing and Managing Biosecurity Threats," Risk Analysis, John Wiley & Sons, vol. 40(11), pages 2462-2477, November.
    18. César Gil & David Rios Insua & Jesus Rios, 2016. "Adversarial Risk Analysis for Urban Security Resource Allocation," Risk Analysis, John Wiley & Sons, vol. 36(4), pages 727-741, April.
    19. David Rios Insua & David Banks & Jesus Rios, 2016. "Modeling Opponents in Adversarial Risk Analysis," Risk Analysis, John Wiley & Sons, vol. 36(4), pages 742-755, April.
    20. Christoph Werner & Tim Bedford & John Quigley, 2018. "Sequential Refined Partitioning for Probabilistic Dependence Assessment," Risk Analysis, John Wiley & Sons, vol. 38(12), pages 2683-2702, December.
    21. González-Ortega, Jorge & Ríos Insua, David & Cano, Javier, 2019. "Adversarial risk analysis for bi-agent influence diagrams: An algorithmic approach," European Journal of Operational Research, Elsevier, vol. 273(3), pages 1085-1096.
    22. G. Quijano, Eduardo & Ríos Insua, David & Cano, Javier, 2018. "Critical networked infrastructure protection from adversaries," Reliability Engineering and System Safety, Elsevier, vol. 179(C), pages 27-36.
    23. Ekin, Tahir & Naveiro, Roi & Ríos Insua, David & Torres-Barrán, Alberto, 2023. "Augmented probability simulation methods for sequential games," European Journal of Operational Research, Elsevier, vol. 306(1), pages 418-430.
    24. Stefan Rass & Sandra König & Stefan Schauer, 2017. "Defending Against Advanced Persistent Threats Using Game-Theory," PLOS ONE, Public Library of Science, vol. 12(1), pages 1-43, January.
    25. Jinshu Cui & Heather Rosoff & Richard S. John, 2016. "Cumulative Response to Sequences of Terror Attacks Varying in Frequency and Trajectory," Risk Analysis, John Wiley & Sons, vol. 36(12), pages 2272-2284, December.

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