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Signaling Security Games with Attack Planner Deception

Author

Listed:
  • Santing He

    (School of Mathematical Sciences, Dalian University of Technology, Dalian 116000, China)

  • Mingchu Li

    (School of Software Technology, Dalian University of Technology, Dalian 116000, China)

  • Runfa Zhang

    (School of Automation and Software Engineering, Shanxi University, Taiyuan 030013, China)

Abstract

This paper studies a class of attack behavior in which adversaries assume the role of initiators, orchestrating and implementing attacks by hiring executors. We examine the dynamics of strategic attacks, modeling the initiator as an attack planner and constructing the interaction with the defender within a defender–attack planner framework. The individuals tasked with executing the attacks are identified as attackers. To ensure the attackers’ adherence to the planner’s directives, we concurrently consider the interests of each attacker by formulating a multi-objective problem. Furthermore, acknowledging the information asymmetry where defenders have incomplete knowledge of the planners’ payments and the attackers’ profiles, and recognizing the planner’s potential to exploit this for strategic deception, we develop a defender–attack planner model with deception based on signaling games. Subsequently, through the analysis of the interaction between the defender and planner, we refine the model into a tri-level programming problem. To address this, we introduce an effective decomposition algorithm leveraging genetic algorithms. Ultimately, our numerical experiments substantiate that the attack planner’s deceptive strategy indeed yield greater benefits.

Suggested Citation

  • Santing He & Mingchu Li & Runfa Zhang, 2024. "Signaling Security Games with Attack Planner Deception," Mathematics, MDPI, vol. 12(16), pages 1-28, August.
  • Handle: RePEc:gam:jmathe:v:12:y:2024:i:16:p:2532-:d:1457656
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    References listed on IDEAS

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    1. Ding, Tao & Yao, Li & Li, Fangxing, 2018. "A multi-uncertainty-set based two-stage robust optimization to defender–attacker–defender model for power system protection," Reliability Engineering and System Safety, Elsevier, vol. 169(C), pages 179-186.
    2. Parajuli, Anubhuti & Kuzgunkaya, Onur & Vidyarthi, Navneet, 2017. "Responsive contingency planning of capacitated supply networks under disruption risks," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 102(C), pages 13-37.
    3. Chao Zhang & Shahrzad Gholami & Debarun Kar & Arunesh Sinha & Manish Jain & Ripple Goyal & Milind Tambe, 2016. "Keeping Pace with Criminals: An Extended Study of Designing Patrol Allocation against Adaptive Opportunistic Criminals," Games, MDPI, vol. 7(3), pages 1-27, June.
    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. Ghorbani-Renani, Nafiseh & González, Andrés D. & Barker, Kash & Morshedlou, Nazanin, 2020. "Protection-interdiction-restoration: Tri-level optimization for enhancing interdependent network resilience," Reliability Engineering and System Safety, Elsevier, vol. 199(C).
    6. Page, F H, Jr, 1991. "Optimal Contract Mechanisms for Principal-Agent Problems with Moral Hazard and Adverse Selection," Economic Theory, Springer;Society for the Advancement of Economic Theory (SAET), vol. 1(4), pages 323-338, October.
    7. Jun Zhuang & Vicki Bier, 2011. "Secrecy And Deception At Equilibrium, With Applications To Anti-Terrorism Resource Allocation," Defence and Peace Economics, Taylor & Francis Journals, vol. 22(1), pages 43-61.
    8. Fakhry, Ramy & Hassini, Elkafi & Ezzeldin, Mohamed & El-Dakhakhni, Wael, 2022. "Tri-level mixed-binary linear programming: Solution approaches and application in defending critical infrastructure," European Journal of Operational Research, Elsevier, vol. 298(3), pages 1114-1131.
    9. Jun Zhuang & Vicki M. Bier, 2010. "Reasons for Secrecy and Deception in Homeland‐Security Resource Allocation," Risk Analysis, John Wiley & Sons, vol. 30(12), pages 1737-1743, December.
    10. Zhang, Chi & Ramirez-Marquez, José Emmanuel & Wang, Jianhui, 2015. "Critical infrastructure protection using secrecy – A discrete simultaneous game," European Journal of Operational Research, Elsevier, vol. 242(1), pages 212-221.
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