УПРАВЛЕНИЕ ИНФОРМАЦИОННОЙ БЕЗОПАСНОСТЬЮ ПЕРСОНАЛЬНЫХ ДАННЫХ С ИСПОЛЬЗОВАНИЕМ НЕЧЕТКОЙ ЛОГИКИ

Abstract

Introduction: to ensure the necessary level of personal data security in computer systems, it is advisable to create an information security management system that would allow you to help choose protective measures for certain input data. Purpose: to develop an algorithm for the personal data protection model that allows considering a set of input factors for making decisions on information security. Methods: it is proposed to use the fuzzy inference apparatus as a mathematical apparatus for describing such a situation. The main advantage of using this mathematical approach in modeling a control system is the description of conditions and methods for solving problems under uncertainty. Results: when building an information security management system, defined a set of rules and study the influence of changes in input variables on a set of protective measures. The model developed on the basis of this algorithm using fuzzy inference identifies the impact of information security threats on decision-making on the choice of measures to protect personal data in a computer system. The result of threat modeling is also planning that illustrate the relationship between the input and output parameters of the model. These planes allow you to determine the management decision on the choice of measures depending on the values of the selected parameters. The paper proposes three thresholds for the values of each of the protective measures, which determine the need for the measures used to neutralize the simulated threats. The influence of input variables on the output values of the constructed model identify a change in the distribution of the terms of the membership functions of the input parameters, the change of which can significantly affect the final decision on information security management. Discussion: the results of the work indicate the need for an adequate description of both the input variables and the response of the output variables of the model to the input variables in order to take effective measures to protect information.