Abstract:
The article considers the process of building an intrusion detection system using intelligent network traffic analysis. The requirements for the developed system of intrusion detection are formulated, as well as its architecture is proposed. As a mechanism for making decisions about the presence of attacks, it is suggested to use methods of inductive machine learning, namely, artificial neural networks. The paper proposes the construction of a neural network model based on a multilayer perceptron, for which the most significant input parameters are determined. The technique of constructing the intelligent network traffic analysis module, its logic of work are considered. The client-server application for network traffic analysis on the generated parameters was developed ang the results of testing are given in the paper. The created module of intelligent network traffic analysis shows high accuracy of attacks identification. To increase the accuracy of network attack classification, in future studies, it is planned to supplement the intelligent network traffic analysis module with other methods of machine learning, in particular, the machine classifier.
Foundation for Assistance to Small Innovative Enterprises within the framework of the International Program ERA.Net RUS
Bibliographic databases:
Document Type:
Article
Language: Russian
Citation:
A. O. Suvorov, V. A. Suvorova, “Intelligent network traffic analysis for computer intrusion detection”, Artificial Intelligence and Decision Making, 2019, no. 1, 62–73