Signaling Security Games with Attack Planner Deception

Santing He (), Mingchu Li and Runfa Zhang
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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

Mathematics, 2024, vol. 12, issue 16, 1-28

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.

Keywords: signaling game; attack planner deception; multi-attackers; multi-objective optimization; tri-level programming; decomposed algorithm; genetic algorithm (search for similar items in EconPapers)
JEL-codes: C (search for similar items in EconPapers)
Date: 2024
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