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Cyber deterrence with imperfect attribution and unverifiable signaling

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  • Welburn, Jonathan
  • Grana, Justin
  • Schwindt, Karen

Abstract

Motivated by the asymmetric information inherent to cyberwarfare, we examine a game of deterrence between an attacker and a defender in which the defender can signal its retaliatory capability but can only imperfectly attribute an attack. We show that there are equilibria in which the defender sends noisy signals to increase its expected payoff. In some equilibria, the defender can use signaling to deter an attacker and increase its payoff. In a different and somewhat counter-intuitive equilibrium, the defender can increase its expected payoff through signaling by luring the attacker to attack more.

Suggested Citation

  • Welburn, Jonathan & Grana, Justin & Schwindt, Karen, 2023. "Cyber deterrence with imperfect attribution and unverifiable signaling," European Journal of Operational Research, Elsevier, vol. 306(3), pages 1399-1416.
    • Handle: RePEc:eee:ejores:v:306:y:2023:i:3:p:1399-1416
    DOI: 10.1016/j.ejor.2022.07.021
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    References listed on IDEAS

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    1. Konrad, Kai A., 2020. "Attacking and defending multiple valuable secrets in a big data world," European Journal of Operational Research, Elsevier, vol. 280(3), pages 1122-1129.
    2. Emir Kamenica & Matthew Gentzkow, 2011. "Bayesian Persuasion," American Economic Review, American Economic Association, vol. 101(6), pages 2590-2615, October.
    3. Liang, Liang & Chen, Jingxian & Siqueira, Kevin, 2020. "Revenge or continued attack and defense in defender–attacker conflicts," European Journal of Operational Research, Elsevier, vol. 287(3), pages 1180-1190.
    4. Zhuang, Jun & Bier, Vicki M. & Alagoz, Oguzhan, 2010. "Modeling secrecy and deception in a multiple-period attacker-defender signaling game," European Journal of Operational Research, Elsevier, vol. 203(2), pages 409-418, June.
    5. Solak, Senay & Zhuo, Yueran, 2020. "Optimal policies for information sharing in information system security," European Journal of Operational Research, Elsevier, vol. 284(3), pages 934-950.
    6. Jesse C. Johnson & Brett Ashley Leeds & Ahra Wu, 2015. "Capability, Credibility, and Extended General Deterrence," International Interactions, Taylor & Francis Journals, vol. 41(2), pages 309-336, March.
    7. Levitin, Gregory & Hausken, Kjell, 2009. "False targets efficiency in defense strategy," European Journal of Operational Research, Elsevier, vol. 194(1), pages 155-162, April.
    8. Baliga, Sandeep & Bueno De Mesquita, Ethan & Wolitzky, Alexander, 2020. "Deterrence with Imperfect Attribution," American Political Science Review, Cambridge University Press, vol. 114(4), pages 1155-1178, November.
    9. Cheung, Kam-Fung & Bell, Michael G.H., 2021. "Attacker–defender model against quantal response adversaries for cyber security in logistics management: An introductory study," European Journal of Operational Research, Elsevier, vol. 291(2), pages 471-481.
    10. Simon, Jay & Omar, Ayman, 2020. "Cybersecurity investments in the supply chain: Coordination and a strategic attacker," European Journal of Operational Research, Elsevier, vol. 282(1), pages 161-171.
    11. Vladislav SARAN, 2016. "Media Manipulation And Psychological War In Ukraine And The Republic Of Moldova," CES Working Papers, Centre for European Studies, Alexandru Ioan Cuza University, vol. 8(4), pages 738-752, December.
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    Cited by:

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