Analysis of cybercrimes and security in FinTech industries using the novel concepts of interval-valued complex q-rung orthopair fuzzy relations

Abstract

Modeling the uncertainty has long been a crux for mathematicians which was resolved by the theory of fuzzy sets and logic initiated by Zadeh. Since its introduction, many developments and improvements have been made in the field. This research defines several innovative theories such as the Cartesian product (CP) of interval-valued complex q-rung orthopair fuzzy sets (IVCqROFSs), IVCqROF relations (IVCqROFRs), and their types. After deep analysis, related results and worthwhile properties have been stated. Moreover, a Hasse diagram for IVCqROFR is introduced with its properties. The proposed concepts are capable of modeling a wide range of problems of uncertain nature. The involvement of complex numbers enables these structures to cope with phase-altering problems and multidimensional problems, ultimately making them extremely powerful tools for handling ambiguity. An application has been proposed as an illustration. Since, in modern days, every business and industry is being digitalized, the business and finance departments are no exception. Digital systems have numerous risks and threats. Henceforth, for the first time in the theory of fuzzy logic, cybercrimes and cyber security in the industry of FinTech have been modeled and analyzed through fuzzy mathematics. The effects of different cybersecurity techniques on different threats in FinTech are analyzed by using the proposed methods. Finally, the selection and use of the proposed theories in the analysis of Fintech cybersecurity is justified and explained in contrast to other available competing fuzzy structures in the literature.