• Mikhail P. Bazilevskiy, Irkutsk state transport university (Irkutsk, Russia)
• Anna E. Shamanova, Irkutsk state transport university (Irkutsk, Russia)

Ensuring a high level of information security for the tax authorities of the Russian Federation is an urgent task. Leaks of personal data from tax service systems can cause serious harm to both individuals and legal entities. Quite often, such leaks occur due to the fault of employees. So it is important to constantly carry out work aimed at improving the computer literacy of tax authorities’ users in the field of handling protected information. The purpose of this work is to construct a logistic regression model for the competence of specialists in information security issues at one tax service in the Irkutsk region. When modeling to identify unknown parameters in logistic regressions, maximum likelihood method and method based on solving linear programming problem were used. To verify the models, a classification accuracy criterion was used as well as ROC analysis elements in the form of curves reflecting a compromise between sensitivity and specificity at different classification thresholds. The interpretation of regression estimates was carried out using the odds ratio. Specialized tests were developed to assess the degree of competence of employees in the tax service. The results of model identification showed that the method based on linear programming had better classification accuracy in all cases compared to the maximum likelihood method. The best logistic regression revealed the factors that have the greatest impact on the level of competence among tax service employees. This made it possible to develop training materials for specific categories of employees. As a result of the training events, the number of employees who successfully overcame the 70% threshold increased from 90 to 150 out of a total of 160 people.

information security, tax service, logistic regression, maximum likelihood method, linear programming, ROC analysis

2025-12-01