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Risk mitigation strategies for critical infrastructures based on graph centrality analysis

Author

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  • Stergiopoulos, George
  • Kotzanikolaou, Panayiotis
  • Theocharidou, Marianthi
  • Gritzalis, Dimitris

Abstract

Dependency risk graphs have been proposed as a tool for analyzing cascading failures due to critical infrastructure dependency chains. However, dependency chain analysis is not by itself adequate to develop an efficient risk mitigation strategy – one that specifies which critical infrastructures should have high priority for applying mitigation controls in order to achieve an optimal reduction in the overall risk. This paper extends previous dependency risk analysis research to implement efficient risk mitigation. This is accomplished by exploring the relation between dependency risk paths and graph centrality characteristics. Graph centrality metrics are applied to design and evaluate the effectiveness of alternative risk mitigation strategies. The experimental evaluations are based on random graphs that simulate common critical infrastructure dependency characteristics as identified by recent empirical studies. The experimental results are used to specify an algorithm that prioritizes critical infrastructure nodes for applying controls in order to achieve efficient risk mitigation.

Suggested Citation

  • Stergiopoulos, George & Kotzanikolaou, Panayiotis & Theocharidou, Marianthi & Gritzalis, Dimitris, 2015. "Risk mitigation strategies for critical infrastructures based on graph centrality analysis," International Journal of Critical Infrastructure Protection, Elsevier, vol. 10(C), pages 34-44.
    • Handle: RePEc:eee:ijocip:v:10:y:2015:i:c:p:34-44
    DOI: 10.1016/j.ijcip.2015.05.003
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    Cited by:

    1. Molina-Solana, Miguel & Ros, María & Ruiz, M. Dolores & Gómez-Romero, Juan & Martin-Bautista, M.J., 2017. "Data science for building energy management: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 70(C), pages 598-609.
    2. Williams, James Bryan, 2021. "Critical flow centrality measures on interdependent networks with time-varying demands," International Journal of Critical Infrastructure Protection, Elsevier, vol. 35(C).
    3. 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).
    4. Li, Zhitao & Tang, Jinjun & Zhao, Chuyun & Gao, Fan, 2023. "Improved centrality measure based on the adapted PageRank algorithm for urban transportation multiplex networks," Chaos, Solitons & Fractals, Elsevier, vol. 167(C).
    5. Faramondi, Luca & Setola, Roberto & Panzieri, Stefano & Pascucci, Federica & Oliva, Gabriele, 2018. "Finding critical nodes in infrastructure networks," International Journal of Critical Infrastructure Protection, Elsevier, vol. 20(C), pages 3-15.
    6. Yang, Zhen & Dong, Xiaobin & Guo, Li, 2023. "Scenario inference model of urban metro system cascading failure under extreme rainfall conditions," Reliability Engineering and System Safety, Elsevier, vol. 229(C).
    7. Tortosa, Leandro & Vicent, Jose F. & Yeghikyan, Gevorg, 2021. "An algorithm for ranking the nodes of multiplex networks with data based on the PageRank concept," Applied Mathematics and Computation, Elsevier, vol. 392(C).
    8. 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).
    9. Palleti, Venkata Reddy & Joseph, Jude Victor & Silva, Arlindo, 2018. "A contribution of axiomatic design principles to the analysis and impact of attacks on critical infrastructures," International Journal of Critical Infrastructure Protection, Elsevier, vol. 23(C), pages 21-32.
    10. Psaltoglou, Artemis & Calle, Eusebi, 2018. "Enhanced connectivity index – A new measure for identifying critical points in urban public transportation networks," International Journal of Critical Infrastructure Protection, Elsevier, vol. 21(C), pages 22-32.
    11. Galbraith, John W. & Iuliani, Luca, 2019. "Measures of robustness for networked critical infrastructure: An empirical comparison on four electrical grids," International Journal of Critical Infrastructure Protection, Elsevier, vol. 27(C).
    12. 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).
    13. Warnier, Martijn & Dulman, Stefan & Koç, Yakup & Pauwels, Eric, 2017. "Distributed monitoring for the prevention of cascading failures in operational power grids," International Journal of Critical Infrastructure Protection, Elsevier, vol. 17(C), pages 15-27.

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