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A fault diagnosis system for interdependent critical infrastructures based on HMMs

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  • Ntalampiras, Stavros
  • Soupionis, Yannis
  • Giannopoulos, Georgios

Abstract

Modern society depends on the smooth functioning of critical infrastructures which provide services of fundamental importance, e.g. telecommunications and water supply. These infrastructures may suffer from faults/malfunctions coming e.g. from aging effects or they may even comprise targets of terrorist attacks. Prompt detection and accommodation of these situations is of paramount significance.

Suggested Citation

  • 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.
    • Handle: RePEc:eee:reensy:v:138:y:2015:i:c:p:73-81
    DOI: 10.1016/j.ress.2015.01.024
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    References listed on IDEAS

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    1. Johansson, Jonas & Hassel, Henrik & Zio, Enrico, 2013. "Reliability and vulnerability analyses of critical infrastructures: Comparing two approaches in the context of power systems," Reliability Engineering and System Safety, Elsevier, vol. 120(C), pages 27-38.
    2. 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.
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    Cited by:

    1. Alkhaleel, Basem A., 2024. "Machine learning applications in the resilience of interdependent critical infrastructure systems—A systematic literature review," International Journal of Critical Infrastructure Protection, Elsevier, vol. 44(C).
    2. Chen, Gaige & Chen, Jinglong & Zi, Yanyang & Miao, Huihui, 2017. "Hyper-parameter optimization based nonlinear multistate deterioration modeling for deterioration level assessment and remaining useful life prognostics," Reliability Engineering and System Safety, Elsevier, vol. 167(C), pages 517-526.
    3. Følstad, Eirik L. & Helvik, Bjarne E., 2016. "The cost for meeting SLA dependability requirements; implications for customers and providers," Reliability Engineering and System Safety, Elsevier, vol. 145(C), pages 136-146.
    4. Wu, Shimeng & Jiang, Yuchen & Luo, Hao & Zhang, Jiusi & Yin, Shen & Kaynak, Okyay, 2022. "An integrated data-driven scheme for the defense of typical cyber–physical attacks," Reliability Engineering and System Safety, Elsevier, vol. 220(C).
    5. Zhou, Shenghua & Yang, Yifan & Ng, S. Thomas & Xu, J. Frank & Li, Dezhi, 2020. "Integrating data-driven and physics-based approaches to characterize failures of interdependent infrastructures," International Journal of Critical Infrastructure Protection, Elsevier, vol. 31(C).
    6. Wang, Shuliang & Lv, Wenzhuo & Zhang, Jianhua & Luan, Shengyang & Chen, Chen & Gu, Xifeng, 2021. "Method of power network critical nodes identification and robustness enhancement based on a cooperative framework," Reliability Engineering and System Safety, Elsevier, vol. 207(C).
    7. Suo, Weilan & Wang, Lin & Li, Jianping, 2021. "Probabilistic risk assessment for interdependent critical infrastructures: A scenario-driven dynamic stochastic model," Reliability Engineering and System Safety, Elsevier, vol. 214(C).
    8. Garshasbi, Mohammad Sadeq, 2016. "Fault localization based on combines active and passive measurements in computer networks by ant colony optimization," Reliability Engineering and System Safety, Elsevier, vol. 152(C), pages 205-212.

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