Network Traffic Analysis Based on Machine Learning Methods

Comparison of mining algorithms in the problem of detecting malicious network activity based on machine learning models is performed. A structural diagram of a system for analyzing network traffic in an industrial network based on machine learning methods has been developed. On one of the known datasets (CICIDS17), a series of experiments was carried out on preliminary analysis and preprocessing of features, highlighting the most significant features and building final models of classifiers. The f1-measure score for the committee of classifiers on the test sample is 0.967.