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Improving robustness in interdependent networks under intentional attacks by optimizing intra-link allocation.

Yucheng Hao1, Limin Jia1, Yanhui Wang1

  • 1State Key Laboratory of Rail Traffic Control and Safety, Beijing Jiaotong University, No. 3 Shangyuancun Haidian District, Beijing 100044, China.

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This study introduces a new metric and algorithm to improve the robustness of interdependent networks against attacks. The optimized networks show significantly enhanced resilience, preventing sudden collapses.

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Area of Science:

  • Network Science
  • Complex Systems
  • Cybersecurity

Background:

  • Interdependent networks are vulnerable to targeted attacks, especially on high-degree nodes.
  • Improving network robustness against intentional attacks is crucial for system stability.
  • Existing methods may not sufficiently enhance the resilience of complex network structures.

Purpose of the Study:

  • To develop a novel metric for quantifying the robustness of interdependent networks under intentional attacks.
  • To introduce an improved simulated annealing algorithm (ISAA) for optimizing network robustness.
  • To enhance the resilience of interdependent scale-free networks (ISFNs) against targeted disruptions.

Main Methods:

  • Proposed a new metric to measure network robustness against intentional attacks.
  • Developed an improved simulated annealing algorithm (ISAA) for optimizing intra-link allocation.
  • Compared ISAA with existing algorithms for enhancing interdependent scale-free network (ISFN) robustness.
  • Analyzed network structures using degree and clustering coefficient metrics.

Main Results:

  • The ISAA effectively enhances the robustness of interdependent scale-free networks (ISFNs).
  • Optimized ISFNs demonstrate significantly improved resilience compared to original networks.
  • Disassortative and random coupled ISFNs exhibit no sudden collapse after optimization.
  • Optimized ISFNs reveal an 'onion-like' structure in their subnetworks.

Conclusions:

  • The proposed ISAA is a more effective method for improving ISFN robustness.
  • Optimized ISFNs exhibit enhanced resilience against various attack strategies, including those targeting high-degree nodes, betweenness, and PageRank.
  • The 'onion-like' subnetwork structure contributes to the improved robustness of the optimized networks.