Development of a fuzzy production model for assessing the degree of information security in international cooperation - Mulesa, Oksana; Bohdan, Yurii (Technology audit and production reserves, 2024)
The object of research is the methods of assessing the information security indicator in the process of international cooperation. The problem of unification and simplification of the processes of assessing the degree of information security is considered in order to reduce the involvement of human and material resources in them, using the apparatus of fuzzy set theory to take into account the conclusions of competent experts. A fuzzy production model of assessing the degree of information security is developed, which is based on the use of expert knowledge and fuzzy logic methods. A step-by-step approach is proposed for identifying potential risks, classifying them by categories and calculating influence coefficients. An iterative assessment method is created, which allows obtaining a numerical indicator of the degree of information security. Heuristic rules for determining the effective assessment of the degree of information security are developed, taking into account the criticality factor and influence coefficients of different risk categories. A classification of potential information security risks in international IT projects is proposed. An example of constructing production rules for a fuzzy knowledge base is demonstrated. The results are explained by the use of systems analysis to take into account the relationships between different risk categories and the use of fuzzy logic to work with uncertain and incomplete data. The model is based on production rules that integrate expert judgment and allow for adaptive analysis in changing conditions of international cooperation. The developed model can be used to assess information security in small and medium-sized international projects, where it is necessary to provide a quick and effective assessment of the level of security without involving significant resources. The model is especially useful in conditions where the data is fuzzy or incomplete, and the risks vary depending on the specifics of cooperation between different countries and organizations.