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Identifying vulnerabilities in critical infrastructures by network analysis

Author

Listed:
  • Chi Yung Lam
  • Jiaying Lin
  • Mong Soon Sim
  • Kang Tai

Abstract

By modelling the relationships and how disruption cascades within a complex infrastructure network, vulnerabilities can be identified and recovery/response efforts planned. A simulation approach is applied in this paper to identify critical components in a given infrastructure system represented as a graph comprising nodes and links. The network is modelled using NetLogo, a multi-agent programming environment. One- and two-node attack scenarios are programmed to investigate the impact of different node failures in the network, with the ensuing disruption quantified by a giant component metric. In the one-node attack, the minimum, final and average sizes of the giant component unanimously identified the same critical node while the two-node attack simulation identified different node pairs as critical. Which pair should be considered most critical will depend on policy goals to be met. This simulation approach can aid policymakers in deciding which infrastructures require higher protection and how recovery strategies should be planned.

Suggested Citation

  • Chi Yung Lam & Jiaying Lin & Mong Soon Sim & Kang Tai, 2013. "Identifying vulnerabilities in critical infrastructures by network analysis," International Journal of Critical Infrastructures, Inderscience Enterprises Ltd, vol. 9(3), pages 190-210.
    • Handle: RePEc:ids:ijcist:v:9:y:2013:i:3:p:190-210
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    Citations

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    Cited by:

    1. Lam, C.Y. & Tai, K., 2018. "Modeling infrastructure interdependencies by integrating network and fuzzy set theory," International Journal of Critical Infrastructure Protection, Elsevier, vol. 22(C), pages 51-61.
    2. Hassan Al-Zarooni & Hamdi Bashir, 0. "An integrated ISM fuzzy MICMAC approach for modeling and analyzing electrical power system network interdependencies," International Journal of System Assurance Engineering and Management, Springer;The Society for Reliability, Engineering Quality and Operations Management (SREQOM),India, and Division of Operation and Maintenance, Lulea University of Technology, Sweden, vol. 0, pages 1-23.
    3. Hassan Al-Zarooni & Hamdi Bashir, 2020. "An integrated ISM fuzzy MICMAC approach for modeling and analyzing electrical power system network interdependencies," International Journal of System Assurance Engineering and Management, Springer;The Society for Reliability, Engineering Quality and Operations Management (SREQOM),India, and Division of Operation and Maintenance, Lulea University of Technology, Sweden, vol. 11(6), pages 1204-1226, December.

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