Assessment of information security risks of automated system using neuro-fuzzy logic

Abstract

Objective. Automated systems are widely used in production, and an important criterion for their reliability is information security. The aim of the study is to provide a balance between possible losses as a result of the implementation of threats and the cost of protection tools that reduce risks using neuro-fuzzy logic.Method. The developed model is based on the use of fuzzy logic.Result. A model of integrated information security risk assessment has been obtained, which can be practically applied for a comprehensive analysis of the effectiveness of organizing a protection system for automated systems operating in various fields of activity. The risk indicators of information security of an automated system, described with the help of linguistic variables, are revealed. Based on these indicators, information security risk assessments were obtained from the state of: software; technical support; information support; organizational and methodological support; the level of training and motivation of employees. The fuzzy production rules of the model are formulated to determine the integrated assessment of the information security of an automated system, providing a full account of all factors that have a significant impact on the level of security of an automated system.Conclusions. A feature of the proposed approach is the formalization of the assessment process, reducing the level of subjectivity in the formation of risk assessments.