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Defending Against a Stockpiling Terrorist

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  • Kjell Hausken
  • Jun Zhuang

Abstract

A government defends against a terrorist who attacks repeatedly and stockpiles its resources over time. The government defends an asset and attacks the terrorist's resources. The terrorist defends its resources and attacks the government. We find four possible equilibrium solutions: (1) the government attacks only, deterring the terrorist; (2) both players defend and attack; (3) the government defends but does not attack, and the terrorist attacks only; and (4) the terrorist attacks a passive government. Understanding which factors impact the four cases is important in order to combat terrorism. The terrorist allocates its resources over T periods according to a geometric series with a stockpiling parameter. This article analyzes how the government and terrorist prefer low versus high stockpiling parameters and how these preferences interact with the other parameters such as the terrorist's resources and the players’ asset valuations, unit defense and attack costs, and discount factors. If the terrorist's resources are small, it can be deterred in each period. If the terrorist's resources are extremely large, it allocates its resources equally across the T periods, whereas the government prefers a single attack. If the terrorist's resources are intermediate, the terrorist would be deterred in each period if it allocated its resources equally across the T periods. It thus strikes a balance where it allocates much resources to early or late periods, to facilitate attacks, and accept being deterred in the other periods. As the future becomes less important, the terrorist attacks more in early periods.

Suggested Citation

  • Kjell Hausken & Jun Zhuang, 2011. "Defending Against a Stockpiling Terrorist," The Engineering Economist, Taylor & Francis Journals, vol. 56(4), pages 321-353.
  • Handle: RePEc:taf:uteexx:v:56:y:2011:i:4:p:321-353
    DOI: 10.1080/0013791X.2011.624260
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    Citations

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    Cited by:

    1. Zhang, Jing & Zhuang, Jun & Behlendorf, Brandon, 2018. "Stochastic shortest path network interdiction with a case study of Arizona–Mexico border," Reliability Engineering and System Safety, Elsevier, vol. 179(C), pages 62-73.
    2. Xing Gao & Weijun Zhong & Shue Mei, 2014. "A game-theoretic analysis of information sharing and security investment for complementary firms," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 65(11), pages 1682-1691, November.
    3. Bertrand Crettez & Naila Hayek, 2014. "Terrorists’ Eradication Versus Perpetual Terror War," Journal of Optimization Theory and Applications, Springer, vol. 160(2), pages 679-702, February.
    4. Shan, Xiaojun & Zhuang, Jun, 2018. "Modeling cumulative defensive resource allocation against a strategic attacker in a multi-period multi-target sequential game," Reliability Engineering and System Safety, Elsevier, vol. 179(C), pages 12-26.
    5. Starita, Stefano & Scaparra, Maria Paola, 2016. "Optimizing dynamic investment decisions for railway systems protection," European Journal of Operational Research, Elsevier, vol. 248(2), pages 543-557.
    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. Peiqiu Guan & Jun Zhuang, 2016. "Modeling Resources Allocation in Attacker‐Defender Games with “Warm Up” CSF," Risk Analysis, John Wiley & Sons, vol. 36(4), pages 776-791, April.
    8. Hausken, Kjell & Zhuang, Jun, 2013. "The impact of disaster on the strategic interaction between company and government," European Journal of Operational Research, Elsevier, vol. 225(2), pages 363-376.
    9. Kjell Hausken & Jonathan W. Welburn & Jun Zhuang, 2024. "A Review of Attacker–Defender Games and Cyber Security," Games, MDPI, vol. 15(4), pages 1-27, August.
    10. João Ricardo Faria & Daniel Arce, 2021. "The Path of Terror Attacks," Games, MDPI, vol. 12(2), pages 1-11, April.

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