Improving the Quality of the Identification of the Information Security State Based on Sample Segmentation

Increasing the quality indicators for identifying the information security (IS) state of individual segments of cyber-physical systems is related to processing large information arrays. A method for improving quality indicators when solving problems of identifying the IS state is proposed. Its implementation is based on the formation of individual sample segments. Analysis of the properties of these segments makes it possible to select and assign algorithms that have the best quality indicators in the current segment. Segmentation of a data sample is considered. Using real dataset data as an example, experimental values of the quality indicator for the proposed method are given for various classifiers on individual segments and the entire sample.