Application of homogeneous nested piecewise linear regression with clustering of variables to model staffing levels of information protection units

Abstract

Application of homogeneous nested piecewise linear regression with clustering of variables to model staffing levels of information protection units

Noskov S.I., Medvedev A.P.

Incoming article date: 04.04.2025

Mathematical modeling of complex systems often requires the use of variable grouping methods to build effective models. This paper considers the problem of constructing a homogeneous nested piecewise linear regression with variable grouping for modeling the staffing of information protection units. A corresponding model for the Social Fund of Russia is constructed using spatial data for the year 2022. The data on the number of employees of the organization, electronic signatures, protected nodes, protected resources, the total number of structural units, individual buildings and IT service specialists are used as independent variables.

Keywords: information protection, regression model, homogeneous nested piecewise linear regression, parameter estimation, least modulus method, linear-Boolean programming problem, index set, set power, social fund