Modeling and assessing cyber resilience of smart grid using Bayesian network-based approach: a system of systems problem. Issue 3 (4th April 2020)

• Record Type: Journal Article
• Authors: Ibne Hossain, Niamat Ullah; Nagahi, Morteza; Jaradat, Raed; Shah, Chiranjibi; Buchanan, Randy; Hamilton, Michael
• Is Part Of: Journal of computational design and engineering. Volume 7:Issue 3(2020)
• Page Start: 352
• Page End: 366
• Publication Date: 2020-04-04
• Subjects: cyber vulnerabilities -- smart grid -- power system -- resilience -- Bayesian network -- system of systems; Engineering -- Data processing -- Periodicals; Computer-aided design -- Periodicals; Computer-aided design; Engineering -- Data processing; Electronic journals; Electronic journals; Periodicals; 620.0042
• DOI: 10.1093/jcde/qwaa029
• Languages: English
• ISSNs: 2288-4300

Abstract

Abstract: Due to the widespread of new technologies, the modern electric power system has become much more complex and uncertain. The Integration of technologies in the electric power system has increased the exposure of cyber threats and correlative susceptibilities from malicious cyber-attacks. To better address these cyber risks and minimize the effects of the power system outage, this research identifies the potential causes and mitigation techniques for the smart grid (SG) and assesses the overall cyber resilience of smart grid systems using a Bayesian network approach. Bayesian network is a powerful analytical tool predominantly used in risk, reliability, and resilience assessment under uncertainty. The quantification of the model is examined, and the results are analyzed through different advanced techniques such as predictive inference reasoning and sensitivity analysis. Different scenarios have been developed and analyzed to identify critical variables that are susceptible to the cyber resilience of a smart grid system of systems. Insight drawn from these analyses suggests that overall cyber resilience of the SG system of systems is dependent upon the status of identified factors, and more attention should be directed towards developing the countermeasures against access domain vulnerability. The research also shows the efficacy of a Bayesian network to assess and enhance the overall cyber resilience of the smart grid system of systems. Graphical Abstract: