Optimization of the volume of technical means of machine learning of the information protection system of key systems of information infrastructure

The purpose of this article is to consider the information activities of information security systems of information infrastructures of government agencies processing personal data in order to determine the main approaches to optimizing the volume of technical means of the information security system of information infrastructures using machine learning tools, since within the framework of the traditional approach, information protection is focused mainly on heuristic methods and the use of intuitive assessments of changes in the characteristics of information processes as a result of technical protection measures. Based on the analysis of the organization of information protection of a given level (class) of security of the information system of a government agency, the author substantiates the integrated use of machine learning of the information security system in order to optimally use the functional volume of technical means allocated to ensure a given level (class) of security of the information security system of a government agency processing personal data. The article proposes a number of new approaches to optimizing the volume of technical means of machine learning of an information infrastructure entity processing personal data. The considered results made it possible to formulate the problem of modeling and optimizing the volume of technical means of machine learning of the information security system for the information activities of a government agency in the context of counteracting information leakage through technical channels.