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Research on multi-level container security isolation operation strategy based on static game.

Jiakun Wen1, Yuan Cao2, Yongkui Sun2

  • 1School of Automation and Intelligence, Beijing Jiaotong University, Beijing 100044, China; CRSC Research & Design Institute Group Co. Ltd, Beijing 100070, China.

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|March 7, 2026
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Rail transit passenger services can be secured using cloud-edge computing. A new multi-level container security isolation model and a wolf pack-co-evolution algorithm dynamically adjust strategies to prevent cyber-attacks and data leaks.

Keywords:
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Area of Science:

  • Computer Science
  • Cybersecurity
  • Operations Research

Background:

  • Rail transit passenger services face increasing demands, necessitating advanced computing solutions.
  • Cloud-edge collaborative computing is a growing area for enhancing these services.
  • Securing data and applications within containers in cloud-edge environments is a critical challenge due to open network vulnerabilities and cyber-attacks.

Purpose of the Study:

  • To propose a multi-level container security isolation model for cloud-edge computing environments in passenger service systems.
  • To develop a dynamic security strategy adjustment mechanism to mitigate cyber-attacks.
  • To enhance the security and reliability of applications and data within containers.

Main Methods:

  • A multi-level container security isolation model with configurable security policies was designed.
  • A static game model was employed for dynamic optimization of security strategies.
  • A wolf pack-co-evolution algorithm was integrated to find the optimal solution (Nash equilibrium) for the game.

Main Results:

  • The proposed wolf pack-co-evolution algorithm effectively determines optimal security strategies by solving the static game.
  • Dynamic adjustments to security strategies were achieved, enhancing container security.
  • Simulation experiments validated the effectiveness of the algorithm in ensuring container security and improving computing efficiency.

Conclusions:

  • The developed multi-level container security isolation model and optimization algorithm provide a robust solution for securing cloud-edge computing in passenger services.
  • This approach effectively balances security requirements with computational efficiency.
  • The findings contribute to the advancement of secure and reliable cloud-edge systems for critical infrastructure.