Abstract
Industrial control system (ICS) attacks are usually targeted attacks that use the ICS entry approach to get a foothold within a system and move laterally throughout the organization. In recent decades, powerful attacks such as Stuxnet, Duqu, Flame, and Havex have served as wake-up calls for industrial units. All organizations are faced with the rise of security challenges in technological innovations. This paper aims to develop aggregation operators that can be used to address the decision-making problems based on a spherical fuzzy rough environment. Meanwhile, some interesting properties of idempotence, boundedness, and monotonicity for the proposed operators are analyzed. Moreover, we use this newly constructed framework to select ICS security suppliers and validate its acceptability. Furthermore, a different test has been performed based on a new operator to strengthen the suggested approach. Additionally, comparative analysis based on the novel extended TOPSIS method is presented to demonstrate the superiority of the proposed technique. The results show that the conventional approach has a larger area for information representation, better adaptability to the evaluation environment, and higher reliability of the evaluation results.
Highlights
Many governments are launching initiatives to encourage the implementation of electronic and manufacturing innovations, including Germany’s industry 4.0 systems, the United States’ reindustrialization, and China’s “Made in China 2025” strategy to advance next-generation information technology
Spherical Fuzzy Rough Ordered Weighted Averaging Aggregation Operators. is subsection is devoted for the study of SPROWA aggregation operators, which weigh the ordered position of the argument. en we have presented the fundamental properties of SFROWA operators
Step 1: the expert evaluation matrices under spherical fuzzy rough values are enclosed in Tables 2–4 which is given in real life case study
Summary
Many governments are launching initiatives to encourage the implementation of electronic and manufacturing innovations, including Germany’s industry 4.0 systems, the United States’ reindustrialization, and China’s “Made in China 2025” strategy to advance next-generation information technology. Tang et al [48] proposed the decision-theoretic rough set model with q-rung orthopair fuzzy information, as well as its application in evaluating stock investments. For MADM, Hussain et al [51] presented a covering-based q-rung orthopair fuzzy rough set model hybrid with the TOPSIS approach. These extensions of the q-rung orthopair fuzzy rough set successfully handle DMs’ evaluation values in MAGDM problems. Generalized distance measure is established to find the differences between two SFRSs. In the presented SFR TOPSIS and SFR aggregation operators for solving MAGDM problems, generalized distance measures-based entropy measure is introduced to find out the criteria weights under SFR information used in this paper. (4) comparisons with the spherical fuzzy rough TOPSIS method are made to interpret the outcomes. e ranking of the obtained results is presented graphically
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