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Complexity and Vulnerability Analysis of Critical Infrastructures: A Methodological Approach

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  • Yongliang Deng
  • Liangliang Song
  • Zhipeng Zhou
  • Ping Liu

Abstract

Vulnerability analysis of network models has been widely adopted to explore the potential impacts of random disturbances, deliberate attacks, and natural disasters. However, almost all these models are based on a fixed topological structure, in which the physical properties of infrastructure components and their interrelationships are not well captured. In this paper, a new research framework is put forward to quantitatively explore and assess the complexity and vulnerability of critical infrastructure systems. Then, a case study is presented to prove the feasibility and validity of the proposed framework. After constructing metro physical network (MPN), Pajek is employed to analyze its corresponding topological properties, including degree, betweenness, average path length, network diameter, and clustering coefficient. With a comprehensive understanding of the complexity of MPN, it would be beneficial for metro system to restrain original near-miss or accidents and support decision-making in emergency situations. Moreover, through the analysis of two simulation protocols for system component failure, it is found that the MPN turned to be vulnerable under the condition that the high-degree nodes or high-betweenness edges are attacked. These findings will be conductive to offer recommendations and proposals for robust design, risk-based decision-making, and prioritization of risk reduction investment.

Suggested Citation

  • Yongliang Deng & Liangliang Song & Zhipeng Zhou & Ping Liu, 2017. "Complexity and Vulnerability Analysis of Critical Infrastructures: A Methodological Approach," Mathematical Problems in Engineering, Hindawi, vol. 2017, pages 1-12, October.
  • Handle: RePEc:hin:jnlmpe:8673143
    DOI: 10.1155/2017/8673143
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    Cited by:

    1. Wang, Wenhao & Wang, Yanhui & Wang, Guangxing & Li, Man & Jia, Limin, 2023. "Identification of the critical accident causative factors in the urban rail transit system by complex network theory," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 610(C).

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