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Analyzing vulnerabilities between SCADA system and SUC due to interdependencies

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  • Nan, Cen
  • Eusgeld, Irene
  • Kröger, Wolfgang

Abstract

Interdependencies within and among Critical Infrastructures (CIs), e.g., between Industrial Control Systems (ICSs), in particular Supervisory Control and Data Acquisition (SCADA) system, and the underlying System Under Control (SUC), have dramatically increased the overall complexity of related systems, causing the emergence of unpredictable behaviors and making them more vulnerable to cascading failures. It is vital to get a clear understanding of these often hidden interdependency issues and tackle them with advanced modeling and simulation techniques. In this paper, vulnerabilities due to interdependencies between these two exemplary systems (SCADA and SUC) are investigated and analyzed comprehensively using a modified five-step methodical framework. Furthermore, suggestions for system performance improvements based on the investigation and analysis results, which could be useful to minimize the negative effects and improve their coping capacities, are also presented in this paper.

Suggested Citation

  • Nan, Cen & Eusgeld, Irene & Kröger, Wolfgang, 2013. "Analyzing vulnerabilities between SCADA system and SUC due to interdependencies," Reliability Engineering and System Safety, Elsevier, vol. 113(C), pages 76-93.
    • Handle: RePEc:eee:reensy:v:113:y:2013:i:c:p:76-93
    DOI: 10.1016/j.ress.2012.12.014
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    2. J. S. Busby & B. Green & D. Hutchison, 2017. "Analysis of Affordance, Time, and Adaptation in the Assessment of Industrial Control System Cybersecurity Risk," Risk Analysis, John Wiley & Sons, vol. 37(7), pages 1298-1314, July.
    3. Ouyang, Min, 2014. "Review on modeling and simulation of interdependent critical infrastructure systems," Reliability Engineering and System Safety, Elsevier, vol. 121(C), pages 43-60.
    4. Ntalampiras, Stavros & Soupionis, Yannis & Giannopoulos, Georgios, 2015. "A fault diagnosis system for interdependent critical infrastructures based on HMMs," Reliability Engineering and System Safety, Elsevier, vol. 138(C), pages 73-81.
    5. Galbusera, Luca & Trucco, Paolo & Giannopoulos, Georgios, 2020. "Modeling interdependencies in multi-sectoral critical infrastructure systems: Evolving the DMCI approach," Reliability Engineering and System Safety, Elsevier, vol. 203(C).
    6. Zhao, Chen & Li, Nan & Fang, Dongping, 2018. "Criticality assessment of urban interdependent lifeline systems using a biased PageRank algorithm and a multilayer weighted directed network model," International Journal of Critical Infrastructure Protection, Elsevier, vol. 22(C), pages 100-112.
    7. Quan Mao & Nan Li, 2018. "Assessment of the impact of interdependencies on the resilience of networked critical infrastructure systems," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 93(1), pages 315-337, August.
    8. Nan, Cen & Sansavini, Giovanni, 2015. "Multilayer hybrid modeling framework for the performance assessment of interdependent critical infrastructures," International Journal of Critical Infrastructure Protection, Elsevier, vol. 10(C), pages 18-33.
    9. Ouyang, Min, 2017. "A mathematical framework to optimize resilience of interdependent critical infrastructure systems under spatially localized attacks," European Journal of Operational Research, Elsevier, vol. 262(3), pages 1072-1084.
    10. Shafieezadeh, Abdollah & Ivey Burden, Lindsay, 2014. "Scenario-based resilience assessment framework for critical infrastructure systems: Case study for seismic resilience of seaports," Reliability Engineering and System Safety, Elsevier, vol. 132(C), pages 207-219.
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    12. Nan, Cen & Sansavini, Giovanni, 2017. "A quantitative method for assessing resilience of interdependent infrastructures," Reliability Engineering and System Safety, Elsevier, vol. 157(C), pages 35-53.

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