Evaluating the Impact of Security Risks through Fuzzy AHP-TOPSIS Method

The increasing demand for big data and the depletion of security in data become a critical threat in the digital world. Selecting appropriate information and developing a secure application is a critical task in the software development life cycle (SDLC). This paper shows how the multi-criteria decision-making (MCDM) technique may be used to select appropriate risk factors and define the criteria for the development of software. The proposed model is the integration of two MCDM approaches, i.e., AHP and TOPSIS that are used to calculate the ideal criteria. The appropriate criteria are determined by analyzing risk variables during the requirement engineering stage of the SDLC and their impact on risk attributes. Through the integration of AHP with TOPSIS, an effective pair-wise comparison process and ranking of criteria for optimal and secure software are evaluated in this model. The study presents a novel perspective on the MCDM technique. Furthermore, the security risk's influence on the requirements engineering process was quantified. Practitioners can apply the findings and conclusions to enhance software usability and security.