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Multi-criteria node criticality assessment framework for critical infrastructure networks

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  • Faramondi, Luca
  • Oliva, Gabriele
  • Setola, Roberto

Abstract

Spotting criticalities in Critical Infrastructure networks is a crucial task in order to implement effective protection strategies against exogenous or malicious events. Yet, most of the approaches in the literature focus on specific aspects (e.g., presence of hubs, minimum paths) and there is a need to identify tradeoffs among importance metrics that are typically clashing with each other. In this paper we propose an approach for the assessment of criticalities which combines multi-criteria decision making techniques and topological/dynamical centrality measures. In particular, we resort to the Sparse Analytic Hierarchy Process (SAHP) technique to calculate the relevance of the different metrics based on pairwise comparisons of the metrics by Subject Matter Experts (SMEs) and to merge the different metrics into a holistic indicator of node criticality/importance that takes into account all the metrics. With the aim to experimentally demonstrate the potential of the proposed approach, we consider a case study related to the Central London Tube Network. According to the experimental results, the proposed aggregated ranking exhibits negligible correlation with the single metrics being aggregated, thus suggesting that the proposed approach effectively combines the different metrics into a new perspective.

Suggested Citation

  • Faramondi, Luca & Oliva, Gabriele & Setola, Roberto, 2020. "Multi-criteria node criticality assessment framework for critical infrastructure networks," International Journal of Critical Infrastructure Protection, Elsevier, vol. 28(C).
  • Handle: RePEc:eee:ijocip:v:28:y:2020:i:c:s1874548220300020
    DOI: 10.1016/j.ijcip.2020.100338
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    References listed on IDEAS

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    2. Wang, Shuliang & Sun, Jingya & Zhang, Jianhua & Dong, Qiqi & Gu, Xifeng & Chen, Chen, 2023. "Attack-Defense game analysis of critical infrastructure network based on Cournot model with fixed operating nodes," International Journal of Critical Infrastructure Protection, Elsevier, vol. 40(C).
    3. Zhang, Yifan & Ng, S. Thomas, 2021. "A hypothesis-driven framework for resilience analysis of public transport network under compound failure scenarios," International Journal of Critical Infrastructure Protection, Elsevier, vol. 35(C).
    4. Molinos-Senante, María & Chamorro, Alondra & Contreras, Marta & Echaveguren, Tomas, 2023. "Natural hazard risk management in the Chilean drinking water industry: Diagnosis and recommendations," Utilities Policy, Elsevier, vol. 82(C).
    5. Faramondi, Luca & Oliva, Gabriele & Setola, Roberto & Bozóki, Sándor, 2023. "Robustness to rank reversal in pairwise comparison matrices based on uncertainty bounds," European Journal of Operational Research, Elsevier, vol. 304(2), pages 676-688.
    6. Tornyeviadzi, Hoese Michel & Neba, Fabrice Abunde & Mohammed, Hadi & Seidu, Razak, 2021. "Nodal vulnerability assessment of water distribution networks: An integrated Fuzzy AHP-TOPSIS approach," International Journal of Critical Infrastructure Protection, Elsevier, vol. 34(C).
    7. Wang, Shuliang & Dong, Qiqi, 2023. "A multi-source power grid's resilience enhancement strategy based on subnet division and power dispatch," International Journal of Critical Infrastructure Protection, Elsevier, vol. 41(C).
    8. Franken, Jonas & Reinhold, Thomas & Reichert, Lilian & Reuter, Christian, 2022. "The digital divide in state vulnerability to submarine communications cable failure," International Journal of Critical Infrastructure Protection, Elsevier, vol. 38(C).

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