Information security risk analysis methods: fuzzy logic

A.S. Lyubukhin


This article presents a theoretical study of the applicability of fuzzy set theory for the analysis and assessment of information risks in the course of auditing the security of critical information infrastructure objects. The features of this theory are considered on examples from the subject area of information risks with the construction of a diagram, illustrating the stages of implementation of fuzzy inference. Each of the stages of fuzzy inference is detailed with a transposition to the process of analyzing and evaluating information risks using the example of analyzing information about DDOS attacks on an information system. In the course of the study, the applicability of the fuzzy set theory for solving the problem of analyzing and assessing information risks of critical information infrastructure objects was proved.

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Lyubukhin A.S. Algorithm K-means clustering and mutual information – the best tool for calculating the magnitude of information security risk // Collection of articles on the results of the XXI International Scientific and Practical Conference “Problems of design, application and security of information systems in a digital economy” Publishing house: RSUE (RINH) 2021 p.61-68

Lotfi Zadeh is the father of fuzzy logic. Access mode:

FSTEC Order No. 239 dated December 25, 2017 “On Approval of the Requirements for Ensuring the Security of Significant Objects of the Critical Information Infrastructure of the Russian Federation”

Main types of membership functions Access mode:

Chesalin A.N., Grodzensky S.Ya., Van Ty F., Nilov M.Yu., Agafonov A.N. Technology for risk assessment at product life cycle stages using fuzzy logic – Russian Technological Journal 2020;8(6): 167-183 Access mode

Defuzzification methods Access mode

Khizhnyakov Yu.N. Algorithms for fuzzy, neural and neuro-fuzzy control in real-time systems: textbook Perm Publishing house: PNIPU 2013 p. 127-145


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