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Resource Distribution in Multiple Attacks Against a Single Target

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  • Gregory Levitin
  • Kjell Hausken

Abstract

A target is protected by the defender and attacked by an attacker launching sequential attacks. For each attack, a contest intensity measures whether the agents’ efforts have low or high impact on the target vulnerability (low vs. high contest intensity). Both the defender and the attacker have limited resources. It is assumed that the attacker can observe the outcome of each attack and stop the sequence of attacks when the target is destroyed. Two attacker objectives are considered, that is, to maximize the target vulnerability or to minimize the expected attacker resource expenditure. The article addresses the following three questions: whether the attacker should allocate its entire resource into one large attack or distribute it among several attacks; whether geometrically increasing or decreasing resource distribution into a fixed number of sequential attacks is more beneficial than equal resource distribution; and how the optimal attack strategy depends on the contest intensity.

Suggested Citation

  • Gregory Levitin & Kjell Hausken, 2010. "Resource Distribution in Multiple Attacks Against a Single Target," Risk Analysis, John Wiley & Sons, vol. 30(8), pages 1231-1239, August.
  • Handle: RePEc:wly:riskan:v:30:y:2010:i:8:p:1231-1239
    DOI: 10.1111/j.1539-6924.2010.01410.x
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    References listed on IDEAS

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    Cited by:

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    2. Baba Yumiko, 2012. "A Note on a Comparison of Simultaneous and Sequential Colonel Blotto Games," Peace Economics, Peace Science, and Public Policy, De Gruyter, vol. 18(3), pages 1-6, December.
    3. Peiqiu Guan & Meilin He & Jun Zhuang & Stephen C. Hora, 2017. "Modeling a Multitarget Attacker–Defender Game with Budget Constraints," Decision Analysis, INFORMS, vol. 14(2), pages 87-107, June.
    4. Mohsen Golalikhani & Jun Zhuang, 2011. "Modeling Arbitrary Layers of Continuous‐Level Defenses in Facing with Strategic Attackers," Risk Analysis, John Wiley & Sons, vol. 31(4), pages 533-547, April.
    5. Shakun D. Mago & Roman M. Sheremeta, 2017. "Multi‐battle Contests: An Experimental Study," Southern Economic Journal, John Wiley & Sons, vol. 84(2), pages 407-425, October.
    6. Hu, Xiaoxiao & Xu, Maochao & Xu, Shouhuai & Zhao, Peng, 2017. "Multiple cyber attacks against a target with observation errors and dependent outcomes: Characterization and optimization," Reliability Engineering and System Safety, Elsevier, vol. 159(C), pages 119-133.
    7. Jia, Hao & Skaperdas, Stergios & Vaidya, Samarth, 2013. "Contest functions: Theoretical foundations and issues in estimation," International Journal of Industrial Organization, Elsevier, vol. 31(3), pages 211-222.
    8. Gregory Levitin & Kjell Hausken, 2012. "Resource Distribution in Multiple Attacks with Imperfect Detection of the Attack Outcome," Risk Analysis, John Wiley & Sons, vol. 32(2), pages 304-318, February.
    9. Nicola Dimitri, 2020. "Skills, Efficiency, and Timing in a Simple Attack and Defense Model," Decision Analysis, INFORMS, vol. 17(3), pages 227-234, September.
    10. Cary Deck & Roman Sheremeta, 2010. "Fight or Flight? Defending Against Sequential Attacks in the Game of Siege," Working Papers 10-20, Chapman University, Economic Science Institute.
    11. 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.
    12. Ben Yaghlane, Asma & Azaiez, M. Naceur, 2017. "Systems under attack-survivability rather than reliability: Concept, results, and applications," European Journal of Operational Research, Elsevier, vol. 258(3), pages 1156-1164.
    13. Dan Kovenock & Brian Roberson, 2012. "Strategic Defense And Attack For Series And Parallel Reliability Systems: Comment," Defence and Peace Economics, Taylor & Francis Journals, vol. 23(5), pages 507-515, October.
    14. Di Wu & Xiangbin Yan & Rui Peng & Shaomin Wu, 2020. "Optimal defence-attack strategies between one defender and two attackers," Journal of the Operational Research Society, Taylor & Francis Journals, vol. 71(11), pages 1830-1846, November.
    15. Brian A Jackson & David R Frelinger & Jennifer Kavanagh & Brett A Wallace, 2021. "Adaptation by intelligent adversaries to defensive measures: framing adaptation options and demonstrating assessment of attacker preferences using proxy intelligence data," The Journal of Defense Modeling and Simulation, , vol. 18(2), pages 61-85, April.
    16. 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).
    17. Pei-Yu Chen & Frank Yeong-Sung Lin, 2013. "Recovery and Resource Allocation Strategies to Maximize Mobile Network Survivability by Using Game Theories and Optimization Techniques," Journal of Applied Mathematics, Hindawi, vol. 2013, pages 1-9, September.
    18. Chen Wang & Vicki M. Bier, 2016. "Quantifying Adversary Capabilities to Inform Defensive Resource Allocation," Risk Analysis, John Wiley & Sons, vol. 36(4), pages 756-775, April.
    19. Hannah Lobban & Yasser Almoghathawi & Nazanin Morshedlou & Kash Barker, 2021. "Community vulnerability perspective on robust protection planning in interdependent infrastructure networks," Journal of Risk and Reliability, , vol. 235(5), pages 798-813, October.
    20. Asma Ben Yaghlane & Mohamed Naceur Azaiez, 2019. "System survivability to continuous attacks: A game theoretic setting for constant attack rate processes," Journal of the Operational Research Society, Taylor & Francis Journals, vol. 70(8), pages 1308-1320, August.
    21. Deck, Cary & Sheremeta, Roman, 2012. "Fight or Flight?," MPRA Paper 52130, University Library of Munich, Germany.

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