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A Game‐Theoretical Model to Improve Process Plant Protection from Terrorist Attacks

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  • Laobing Zhang
  • Genserik Reniers

Abstract

The New York City 9/11 terrorist attacks urged people from academia as well as from industry to pay more attention to operational security research. The required focus in this type of research is human intention. Unlike safety‐related accidents, security‐related accidents have a deliberate nature, and one has to face intelligent adversaries with characteristics that traditional probabilistic risk assessment techniques are not capable of dealing with. In recent years, the mathematical tool of game theory, being capable to handle intelligent players, has been used in a variety of ways in terrorism risk assessment. In this article, we analyze the general intrusion detection system in process plants, and propose a game‐theoretical model for security management in such plants. Players in our model are assumed to be rational and they play the game with complete information. Both the pure strategy and the mixed strategy solutions are explored and explained. We illustrate our model by an illustrative case, and find that in our case, no pure strategy but, instead, a mixed strategy Nash equilibrium exists.

Suggested Citation

  • Laobing Zhang & Genserik Reniers, 2016. "A Game‐Theoretical Model to Improve Process Plant Protection from Terrorist Attacks," Risk Analysis, John Wiley & Sons, vol. 36(12), pages 2285-2297, December.
    • Handle: RePEc:wly:riskan:v:36:y:2016:i:12:p:2285-2297
    DOI: 10.1111/risa.12569
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    References listed on IDEAS

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    Cited by:

    1. Stef Janssen & Alexei Sharpanskykh & Richard Curran, 2019. "AbSRiM: An Agent‐Based Security Risk Management Approach for Airport Operations," Risk Analysis, John Wiley & Sons, vol. 39(7), pages 1582-1596, July.
    2. Chen, Chao & Yang, Ming & Reniers, Genserik, 2021. "A dynamic stochastic methodology for quantifying HAZMAT storage resilience," Reliability Engineering and System Safety, Elsevier, vol. 215(C).
    3. Dong, Mingxin & Zhang, Zhen & Liu, Yi & Zhao, Dong Feng & Meng, Yifei & Shi, Jihao, 2023. "Playing Bayesian Stackelberg game model for optimizing the vulnerability level of security incident system in petrochemical plants," Reliability Engineering and System Safety, Elsevier, vol. 235(C).
    4. Rezazadeh, Amirali & Talarico, Luca & Reniers, Genserik & Cozzani, Valerio & Zhang, Laobing, 2019. "Applying game theory for securing oil and gas pipelines against terrorism," Reliability Engineering and System Safety, Elsevier, vol. 191(C).
    5. Zhang, Laobing & Reniers, Genserik & Qiu, Xiaogang, 2019. "Playing chemical plant protection game with distribution-free uncertainties," Reliability Engineering and System Safety, Elsevier, vol. 191(C).
    6. 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.
    7. Chen, Chao & Reniers, Genserik & Khakzad, Nima, 2019. "Integrating safety and security resources to protect chemical industrial parks from man-made domino effects: A dynamic graph approach," Reliability Engineering and System Safety, Elsevier, vol. 191(C).
    8. Zhang, Laobing & Reniers, Genserik & Chen, Bin & Qiu, Xiaogang, 2019. "CCP game: A game theoretical model for improving the scheduling of chemical cluster patrolling," Reliability Engineering and System Safety, Elsevier, vol. 191(C).
    9. Han, Lin & Zhao, Xudong & Chen, Zhilong & Wu, Yipeng & Su, Xiaochao & Zhang, Ning, 2021. "Optimal allocation of defensive resources to defend urban power networks against different types of attackers," International Journal of Critical Infrastructure Protection, Elsevier, vol. 35(C).

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