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Quantitative approach to physical protection systems assessment of critical infrastructure elements: Use case in the Slovak Republic

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  • Kampova, Katarina
  • Lovecek, Tomas
  • Rehak, David

Abstract

The robustness of the critical infrastructure system is determined by the validity and vulnerability of its individual elements and the links between them. For this reason, these elements are the basic building blocks of the system, which must be protected from security threats. The level of their physical protection is currently assessed through quantitative models of physical protection systems (PPS). However, these models are now obsolete because they do not allow the integration of new dynamic parameters. For this reason, the article focuses on the implementation of the Bayesian updating method in the PPS model development, which will allow the exact involvement of new information obtained during the PPS life. The application of Bayesian updating to software tools allows recalculation of individual values of input parameters and thus obtaining increasingly realistic information about the efficiency of the PPS system. This information can be used to modify the structure and adopt protection measures in relation to the set limit values of the output parameters of the security assessment. The created use case shows an example of the procedure of developing and assessing a quantitative PPS model on a selected element of water critical infrastructure using software support.

Suggested Citation

  • Kampova, Katarina & Lovecek, Tomas & Rehak, David, 2020. "Quantitative approach to physical protection systems assessment of critical infrastructure elements: Use case in the Slovak Republic," International Journal of Critical Infrastructure Protection, Elsevier, vol. 30(C).
  • Handle: RePEc:eee:ijocip:v:30:y:2020:i:c:s1874548220300408
    DOI: 10.1016/j.ijcip.2020.100376
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    References listed on IDEAS

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    2. Zou, Bowen & Yang, Ming & Zhang, Yuxin & Benjamin, Emi-Reynolds & Tan, Ke & Wu, Wenfei & Yoshikawa, Hidekazu, 2018. "Evaluation of vulnerable path: Using heuristic path-finding algorithm in physical protection system of nuclear power plant," International Journal of Critical Infrastructure Protection, Elsevier, vol. 23(C), pages 90-99.
    3. Rehak, David & Senovsky, Pavel & Hromada, Martin & Lovecek, Tomas, 2019. "Complex approach to assessing resilience of critical infrastructure elements," International Journal of Critical Infrastructure Protection, Elsevier, vol. 25(C), pages 125-138.
    4. Misuri, Alessio & Khakzad, Nima & Reniers, Genserik & Cozzani, Valerio, 2019. "A Bayesian network methodology for optimal security management of critical infrastructures," Reliability Engineering and System Safety, Elsevier, vol. 191(C).
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    Cited by:

    1. David Rehak & Simona Slivkova & Heidi Janeckova & Dominika Stuberova & Martin Hromada, 2022. "Strengthening Resilience in the Energy Critical Infrastructure: Methodological Overview," Energies, MDPI, vol. 15(14), pages 1-14, July.
    2. Katerina Vichova & Martin Hromada & Martin Dzermansky & Lukas Snopek & Robert Pekaj, 2022. "Solving Power Outages in Healthcare Facilities: Algorithmisation and Assessment of Preparedness," Energies, MDPI, vol. 16(1), pages 1-14, December.
    3. Yang, Jun & Huang, Leixiong & Ma, Haoming & Xu, Zhihui & Yang, Ming & Guo, Shaoqiang, 2022. "A 2D-graph model-based heuristic approach to visual backtracking security vulnerabilities in physical protection systems," International Journal of Critical Infrastructure Protection, Elsevier, vol. 38(C).
    4. Michaela Kollarova & Tomas Granak & Stanislava Strelcova & Jozef Ristvej, 2023. "Conceptual Model of Key Aspects of Security and Privacy Protection in a Smart City in Slovakia," Sustainability, MDPI, vol. 15(8), pages 1-19, April.

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