INFORMATION SECURITY RISK ASSESSMENT USING A FUZZY FIS MODEL

Abstract

This article examines the scientific and practical aspects of applying a fuzzy logic–based model to assess information security risks. The relevance of the study is determined by the need for accurate risk evaluation under uncertainty and incomplete data typical of modern information systems. The aim of the work is to develop a fuzzy logic inference model based on the Mamdani method and to demonstrate its effectiveness compared to traditional approaches. The research employs analytical review, modeling, fuzzification, rule-base construction, and experimental validation. The obtained results show that the proposed model provides more accurate risk assessment, effectively handles uncertainty, and is suitable for practical use. The scientific novelty lies in the development of an integrated risk assessment model built upon a system of fuzzy rules. The application of the model in corporate and educational systems confirms its effectiveness as a tool for supporting decision-making in information security management