Identification and selection of systems security engineering approach via bipolar fuzzy multi-criteria decision-making technique based on generalized power operators

Organizations need to choose an appropriate systems security engineering approach to enable them to design and create systems that are secure and resistant to threats in areas where the impacts of security threats are severe. However, this decision-making process may inherently contain bipolarity and vagueness because the criteria used to evaluate systems security engineering approaches may have positive and negative aspects (characteristics). Overlooking these bipolar aspects may result in inadequate or skewed assessments of the risks, which in turn will hamper the ability to address them appropriately. In response to this challenge, this research develops a new methodological framework that combines bipolar fuzzy set theory and generalized power aggregation operators into multi-criteria decision-making for choosing systems security engineering approaches. This new mathematical framework would be known as the bipolar fuzzy multi-criteria decision-making technique and is applicable to solve all sorts of multi-criteria decision-making dilemmas, where bipolarity is involved such as selection of systems security engineering, selection of artificial intelligence models, etc. Thus, further, this manuscript analyzes and solves a case study of the identification and selection of the finest systems security engineering approach through a bipolar fuzzy multi-criteria decision-making technique. To reveal the benefits and supremacy of the initiated technique over the existing ones, this manuscript contains a comparative analysis.