Journal
ENERGIES
Volume 15, Issue 1, Pages -Publisher
MDPI
DOI: 10.3390/en15010218
Keywords
hesitant fuzzy; AHP; fuzzy TOPSIS; cybersecurity; cyber-attack; industrial control systems; security assessment
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Monitoring and control systems in the energy sector are crucial for ensuring the operation of important infrastructures. This research evaluates the cyber security assessments of industrial control systems using hesitant fuzzy-based Analytic Hierarchy Process (AHP) and Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS), identifying the most effective cyber security projects.
Monitoring and control systems in the energy sector are specialized information structures that are not governed by the same information technology standards as the rest of the world's information systems. Such industrial control systems are also used to handle important infrastructures, including smart grids, oil and gas facilities, nuclear power plants, water management systems, and so on. Industry equipment is handled by systems connected to the internet, either via wireless or cable connectivity, in the present digital age. Further, the system must work without fail, with the system's availability rate being of paramount importance. Furthermore, to certify that the system is not subject to a cyber-attack, the entire system must be safeguarded against cyber security vulnerabilities, threats, and hazards. In addition, the article looks at and evaluates cyber security evaluations for industrial control systems, as well as their possible impact on the accessibility of industrial control system operations in the energy sector. This research work discovers that the hesitant fuzzy-based method of the Analytic Hierarchy Process (AHP) and the Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) is an operational procedure for estimating industrial control system cyber security assessments by understanding the numerous characteristics and their impacts on cyber security industrial control systems. The author evaluated the outputs of six distinct projects to determine the quality of the outcomes and their sensitivity. According to the results of the robustness analysis, alternative 1 shows the utmost effective cybersecurity project for the industrial control system. This research work will be a conclusive reference for highly secure and managed monitoring and control systems.
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