A research on network intrusion detection systems using machine learning techniques

Abstract

The article gives a general idea of intrusion detection systems (IDS) and machine learning, presents a classification of machine learning methods. The most commonly used data sets for training IDS are considered. The main performance indicators used to assess the IDS are described. A review of modern research on the development of intrusion detection methods using machine learning is made, the strengths and weaknesses of each solution are described. The data sets used in them, the obtained estimates of the effectiveness of the proposed intrusion detection methods, are analyzed. Based on the results of the analysis, development trends, unresolved problems and promising areas of research were identified.