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Considering the human operator cognitive process for the interpretation of diagnostic outcomes related to component failures and cyber security attacks

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  • Wang, Wei
  • Di Maio, Francesco
  • Zio, Enrico

Abstract

In this work, we consider diagnostics of cyber attacks in Cyber-Physical Systems (CPSs), based on data analytics. For the first time to authors knowledge, the performance of such diagnosis is quantified considering the possible failure of the human operator cognitive process in interpreting and understanding the diagnosis support tool outcomes.

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  • Wang, Wei & Di Maio, Francesco & Zio, Enrico, 2020. "Considering the human operator cognitive process for the interpretation of diagnostic outcomes related to component failures and cyber security attacks," Reliability Engineering and System Safety, Elsevier, vol. 202(C).
    • Handle: RePEc:eee:reensy:v:202:y:2020:i:c:s0951832020305081
    DOI: 10.1016/j.ress.2020.107007
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    References listed on IDEAS

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    1. Wang, Wei & Cammi, Antonio & Di Maio, Francesco & Lorenzi, Stefano & Zio, Enrico, 2018. "A Monte Carlo-based exploration framework for identifying components vulnerable to cyber threats in nuclear power plants," Reliability Engineering and System Safety, Elsevier, vol. 175(C), pages 24-37.
    2. Zio, E., 2018. "The future of risk assessment," Reliability Engineering and System Safety, Elsevier, vol. 177(C), pages 176-190.
    3. Zwirglmaier, Kilian & Straub, Daniel & Groth, Katrina M., 2017. "Capturing cognitive causal paths in human reliability analysis with Bayesian network models," Reliability Engineering and System Safety, Elsevier, vol. 158(C), pages 117-129.
    4. R. Piccinelli & G. Sansavini & R. Lucchetti & E. Zio, 2017. "A General Framework for the Assessment of Power System Vulnerability to Malicious Attacks," Risk Analysis, John Wiley & Sons, vol. 37(11), pages 2182-2190, November.
    5. Park, Jinkyun & Jung, Jae-Yoon & Jung, Wondea, 2016. "The use of a process mining technique to characterize the work process of main control room crews: A feasibility study," Reliability Engineering and System Safety, Elsevier, vol. 154(C), pages 31-41.
    6. Kim, Hee Eun & Son, Han Seong & Kim, Jonghyun & Kang, Hyun Gook, 2017. "Systematic development of scenarios caused by cyber-attack-induced human errors in nuclear power plants," Reliability Engineering and System Safety, Elsevier, vol. 167(C), pages 290-301.
    7. Kim, Yochan & Park, Jinkyun & Jung, Wondea, 2017. "A quantitative measure of fitness for duty and work processes for human reliability analysis," Reliability Engineering and System Safety, Elsevier, vol. 167(C), pages 595-601.
    8. Mkrtchyan, L. & Podofillini, L. & Dang, V.N., 2016. "Methods for building Conditional Probability Tables of Bayesian Belief Networks from limited judgment: An evaluation for Human Reliability Application," Reliability Engineering and System Safety, Elsevier, vol. 151(C), pages 93-112.
    9. Levitin, Gregory & Hausken, Kjell, 2009. "Parallel systems under two sequential attacks," Reliability Engineering and System Safety, Elsevier, vol. 94(3), pages 763-772.
    10. Kim, Man Cheol & Seong, Poong Hyun, 2008. "A method for identifying instrument faults in nuclear power plants possibly leading to wrong situation assessment," Reliability Engineering and System Safety, Elsevier, vol. 93(2), pages 316-324.
    11. Lee, Seung Jun & Kim, Man Cheol & Seong, Poong Hyun, 2008. "An analytical approach to quantitative effect estimation of operation advisory system based on human cognitive process using the Bayesian belief network," Reliability Engineering and System Safety, Elsevier, vol. 93(4), pages 567-577.
    12. Baraldi, Piero & Podofillini, Luca & Mkrtchyan, Lusine & Zio, Enrico & Dang, Vinh N., 2015. "Comparing the treatment of uncertainty in Bayesian networks and fuzzy expert systems used for a human reliability analysis application," Reliability Engineering and System Safety, Elsevier, vol. 138(C), pages 176-193.
    13. Mkrtchyan, L. & Podofillini, L. & Dang, V.N., 2015. "Bayesian belief networks for human reliability analysis: A review of applications and gaps," Reliability Engineering and System Safety, Elsevier, vol. 139(C), pages 1-16.
    14. Groth, Katrina M. & Swiler, Laura P., 2013. "Bridging the gap between HRA research and HRA practice: A Bayesian network version of SPAR-H," Reliability Engineering and System Safety, Elsevier, vol. 115(C), pages 33-42.
    15. Kim, Yochan & Park, Jinkyun & Jung, Wondea & Choi, Sun Yeong & Kim, Seunghwan, 2018. "Estimating the quantitative relation between PSFs and HEPs from full-scope simulator data," Reliability Engineering and System Safety, Elsevier, vol. 173(C), pages 12-22.
    16. Kriaa, Siwar & Pietre-Cambacedes, Ludovic & Bouissou, Marc & Halgand, Yoran, 2015. "A survey of approaches combining safety and security for industrial control systems," Reliability Engineering and System Safety, Elsevier, vol. 139(C), pages 156-178.
    17. Aven, Terje, 2009. "Identification of safety and security critical systems and activities," Reliability Engineering and System Safety, Elsevier, vol. 94(2), pages 404-411.
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    1. Hao, Zhaojun & Di Maio, Francesco & Zio, Enrico, 2023. "A sequential decision problem formulation and deep reinforcement learning solution of the optimization of O&M of cyber-physical energy systems (CPESs) for reliable and safe power production and supply," Reliability Engineering and System Safety, Elsevier, vol. 235(C).
    2. 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).
    3. Liu, Jianqiao & Zou, Yanhua & Wang, Wei & Zio, Enrico & Yuan, Chengwei & Wang, Taorui & Jiang, Jianjun, 2022. "A Bayesian belief network framework for nuclear power plant human reliability analysis accounting for dependencies among performance shaping factors," Reliability Engineering and System Safety, Elsevier, vol. 228(C).
    4. Patriarca, Riccardo & Simone, Francesco & Di Gravio, Giulio, 2022. "Modelling cyber resilience in a water treatment and distribution system," Reliability Engineering and System Safety, Elsevier, vol. 226(C).

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