Geometric Bonferroni Aggregation Operators for Complex Interval-Valued Intuitionistic Fuzzy Aggregation Operators and Their Applications to Cybersecurity Tools Selection

Abstract

Cybersecurity tools selection is a specialized and efficient approach that deals with protecting computer networks, systems, data, and digital infrastructures from harm, malicious assaults, and unauthorized access. This paper aims to develop an innovative selection method for cybersecurity problems using proposed aggregation operators (AOs) and distance measures (DMs) in the environment of complex interval-valued intuitionistic fuzzy sets (CIVIFSs). First, we introduce novel Bonferroni operational laws for CIVIFSs. Then, some novel AOs, called complex interval-valued intuitionistic fuzzy geometric Bonferroni AOs (CIVIFGBAOs) and complex interval-valued intuitionistic fuzzy weighted geometric Bonferroni AOs (CIVIFWGBAOs), are derived using Bonferroni operational laws. The essential properties such as monotonicity, idempotency, and boundness are examined and demonstrated. Further, we propose innovative DMs for CIVIFSs and discuss their fundamental properties. A novel decision-making (D-making) approach is formulated considering the proposed techniques of AOs and DMs. We considered cybersecurity problems based on the proposed D-making technique. We used the proposed CIVIFGBAOs, CIVIFWGBAOs, and DMs for the selection of cybersecurity tools. Moreover, the newly defined approaches are evaluated and compared with some established approaches. To demonstrate this, the ranking results of the proposed techniques are compared with those of the existing methods to present the supremacy and dominance of the newly defined methods. Our proposed approach ranks $\Breve{A}_{3}$ as the most suitable option, achieving a score function 0.513 and 0.57 based on CIVIFGBAOs and CIVIFWGBAOs. It provides better results than existing models.