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Assessing n-order dependencies between critical infrastructures

Author

Listed:
  • Panayiotis Kotzanikolaou
  • Marianthi Theoharidou
  • Dimitris Gritzalis

Abstract

The protection of critical infrastructures (CI) is a complex task, since it involves the assessment of both internal and external security risk. In the recent literature, methodologies have been proposed that can be used to identify organisation-wise security threats, or even first-order dependency risk (i.e., risk deriving from direct dependencies). However, there is a lack of work in the area of multi-order dependencies, i.e., assessing the cumulative effects of a single incident, on infrastructures that are connected indirectly. In this paper, we propose a method to identify and assess multi-order dependencies. Based on previous work, we utilise existing first-order dependency graphs, in order to assess the effect of a disruption to consequent infrastructures. In this way, it may be possible to identify and prevent security threats of very high impact from a macroscopic view, which would be hard to identify if we only examine first-order dependencies. We also present a scenario, which provides some evidence on the applicability of the proposed approach.

Suggested Citation

  • Panayiotis Kotzanikolaou & Marianthi Theoharidou & Dimitris Gritzalis, 2013. "Assessing n-order dependencies between critical infrastructures," International Journal of Critical Infrastructures, Inderscience Enterprises Ltd, vol. 9(1/2), pages 93-110.
  • Handle: RePEc:ids:ijcist:v:9:y:2013:i:1/2:p:93-110
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    Citations

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    Cited by:

    1. Stergiopoulos, George & Kotzanikolaou, Panayiotis & Theocharidou, Marianthi & Lykou, Georgia & Gritzalis, Dimitris, 2016. "Time-based critical infrastructure dependency analysis for large-scale and cross-sectoral failures," International Journal of Critical Infrastructure Protection, Elsevier, vol. 12(C), pages 46-60.
    2. Calvo-Pardo, Hector & Mancini, Tullio & Olmo, Jose, 2021. "Granger causality detection in high-dimensional systems using feedforward neural networks," International Journal of Forecasting, Elsevier, vol. 37(2), pages 920-940.
    3. Martinez-Pastor, Beatriz & Nogal, Maria & O’Connor, Alan & Teixeira, Rui, 2022. "Identifying critical and vulnerable links: A new approach using the Fisher information matrix," International Journal of Critical Infrastructure Protection, Elsevier, vol. 39(C).
    4. Corinna Köpke & Jennifer Mielniczek & Christoph Roller & Kerstin Lange & Frank Sill Torres & Alexander Stolz, 2023. "Resilience management processes in the offshore wind industry: schematization and application to an export-cable attack," Environment Systems and Decisions, Springer, vol. 43(2), pages 161-177, June.
    5. Klein, Peter & Klein, Fabian, 2019. "Dynamics of interdependent critical infrastructures – A mathematical model with unexpected results," International Journal of Critical Infrastructure Protection, Elsevier, vol. 24(C), pages 69-77.
    6. Katina, Polinpapilinho F. & Ariel Pinto, C. & Bradley, Joseph M. & Hester, Patrick T., 2014. "Interdependency-induced risk with applications to healthcare," International Journal of Critical Infrastructure Protection, Elsevier, vol. 7(1), pages 12-26.
    7. Luiijf, Eric & Klaver, Marieke, 2021. "Analysis and lessons identified on critical infrastructures and dependencies from an empirical data set," International Journal of Critical Infrastructure Protection, Elsevier, vol. 35(C).
    8. Stefan Schauer & Nineta Polemi & Haralambos Mouratidis, 2019. "MITIGATE: a dynamic supply chain cyber risk assessment methodology," Journal of Transportation Security, Springer, vol. 12(1), pages 1-35, June.
    9. Tsavdaroglou, Margarita & Al-Jibouri, Saad H.S. & Bles, Thomas & Halman, Johannes I.M., 2018. "Proposed methodology for risk analysis of interdependent critical infrastructures to extreme weather events," International Journal of Critical Infrastructure Protection, Elsevier, vol. 21(C), pages 57-71.
    10. König, Sandra & Rass, Stefan & Schauer, Stefan, 2019. "Cyber-attack impact estimation for a port," Chapters from the Proceedings of the Hamburg International Conference of Logistics (HICL), in: Jahn, Carlos & Kersten, Wolfgang & Ringle, Christian M. (ed.), Digital Transformation in Maritime and City Logistics: Smart Solutions for Logistics. Proceedings of the Hamburg International Conference of Logistics, volume 28, pages 164-183, Hamburg University of Technology (TUHH), Institute of Business Logistics and General Management.

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