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Infrastructure security games

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  • Baykal-Gürsoy, Melike
  • Duan, Zhe
  • Poor, H. Vincent
  • Garnaev, Andrey

Abstract

Infrastructure security against possible attacks involves making decisions under uncertainty. This paper presents game theoretic models of the interaction between an adversary and a first responder in order to study the problem of security within a transportation infrastructure. The risk measure used is based on the consequence of an attack in terms of the number of people affected or the occupancy level of a critical infrastructure, e.g. stations, trains, subway cars, escalators, bridges, etc. The objective of the adversary is to inflict the maximum damage to a transportation network by selecting a set of nodes to attack, while the first responder (emergency management center) allocates resources (emergency personnel or personnel-hours) to the sites of interest in an attempt to find the hidden adversary. This paper considers both static and dynamic, in which the first responder is mobile, games. The unique equilibrium strategy pair is given in closed form for the simple static game. For the dynamic game, the equilibrium for the first responder becomes the best patrol policy within the infrastructure. This model uses partially observable Markov decision processes (POMDPs) in which the payoff functions depend on an exogenous people flow, and thus, are time varying. A numerical example illustrating the algorithm is presented to evaluate an equilibrium strategy pair.

Suggested Citation

  • Baykal-Gürsoy, Melike & Duan, Zhe & Poor, H. Vincent & Garnaev, Andrey, 2014. "Infrastructure security games," European Journal of Operational Research, Elsevier, vol. 239(2), pages 469-478.
  • Handle: RePEc:eee:ejores:v:239:y:2014:i:2:p:469-478
    DOI: 10.1016/j.ejor.2014.04.033
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    2. Yolmeh, Abdolmajid & Baykal-Gürsoy, Melike, 2021. "Weighted network search games with multiple hidden objects and multiple search teams," European Journal of Operational Research, Elsevier, vol. 289(1), pages 338-349.
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    4. Karwowski, Jan & Mańdziuk, Jacek, 2019. "A Monte Carlo Tree Search approach to finding efficient patrolling schemes on graphs," European Journal of Operational Research, Elsevier, vol. 277(1), pages 255-268.
    5. Nguyen, Di H. & Smith, J. Cole, 2022. "Network interdiction with asymmetric cost uncertainty," European Journal of Operational Research, Elsevier, vol. 297(1), pages 239-251.
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    7. Katerina Papadaki & Steve Alpern & Thomas Lidbetter & Alec Morton, 2016. "Patrolling a Border," Operations Research, INFORMS, vol. 64(6), pages 1256-1269, December.
    8. Wei, Ningji & Walteros, Jose L., 2022. "Integer programming methods for solving binary interdiction games," European Journal of Operational Research, Elsevier, vol. 302(2), pages 456-469.
    9. Sushil Gupta & Martin K. Starr & Reza Zanjirani Farahani & Mahsa Mahboob Ghodsi, 2020. "Prevention of Terrorism–An Assessment of Prior POM Work and Future Potentials," Production and Operations Management, Production and Operations Management Society, vol. 29(7), pages 1789-1815, July.
    10. Matthews, Logan R. & Gounaris, Chrysanthos E. & Kevrekidis, Ioannis G., 2019. "Designing networks with resiliency to edge failures using two-stage robust optimization," European Journal of Operational Research, Elsevier, vol. 279(3), pages 704-720.
    11. Li, Yulong & Lin, Jie & Zhang, Chi & Zhu, Huaxing & Zeng, Saixing & Sun, Chengshaung, 2022. "Joint optimization of structure and protection of interdependent infrastructure networks," Reliability Engineering and System Safety, Elsevier, vol. 218(PB).
    12. Khouzani, MHR. & Liu, Zhengliang & Malacaria, Pasquale, 2019. "Scalable min-max multi-objective cyber-security optimisation over probabilistic attack graphs," European Journal of Operational Research, Elsevier, vol. 278(3), pages 894-903.
    13. Hunt, Kyle & Zhuang, Jun, 2024. "A review of attacker-defender games: Current state and paths forward," European Journal of Operational Research, Elsevier, vol. 313(2), pages 401-417.

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