Evolutionary Game Theory Research on Security Regulation Strategies for Critical Information Infrastructure from a Collaborative Perspective

Background/Problem] Digital transformation has exposed critical information infrastructure to increasingly sophisticated security threats, rendering traditional regulatory models inadequate. Conducting evolutionary game analysis on security regulation strategies for critical information infrastructure—to elucidate the interaction mechanisms between regulatory policies and security behaviors—has emerged as a pivotal issue for enhancing governance efficacy. [Methods/Process] Building upon an applicability analysis of evolutionary game theory for critical information infrastructure security regulation, this study establishes fundamental assumptions and parameter configurations. A two-party evolutionary game model is constructed from a collaborative perspective, involving both infrastructure operators and government regulators, followed by an analysis of behavioral strategies and the stability of the game system. [Results/Conclusions] The study reveals that an ideal equilibrium is achieved when the benefits of enhanced security management outweigh the costs for operators. Key influencing factors include regulatory costs, enforcement effectiveness, management expenditures, accident probabilities, penalty severity, incentive values, and potential gains from non-compliance. These findings provide actionable insights for optimizing regulatory frameworks.

• Publication year

  2025

• Venue

  2025 2nd International Symposium on AI and Cybersecurity (ISAICS)

• Publication date

  2025-10-24

• Fields of study

  Not labeled

• Identifiers
  DOI 10.1109/ISAICS66888.2025.11350239
• External record

  Open on Semantic Scholar

• Source metadata

  Semantic Scholar

• No claims are published for this paper.

• No concepts are published for this paper.

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