Artificial Intelligence and Decision Making
RUS  ENG    JOURNALS   PEOPLE   ORGANISATIONS   CONFERENCES   SEMINARS   VIDEO LIBRARY   PACKAGE AMSBIB  
General information
Latest issue
Archive
Guidelines for authors

Search papers
Search references

RSS
Latest issue
Current issues
Archive issues
What is RSS



Artificial Intelligence and Decision Making:
Year:
Volume:
Issue:
Page:
Find






Personal entry:
Login:
Password:
Save password
Enter
Forgotten password?
Register


Artificial Intelligence and Decision Making, 2019, Issue 1, Pages 62–73
DOI: https://doi.org/10.14357/20718594190106
(Mi iipr162)
 

This article is cited in 1 scientific paper (total in 1 paper)

Information protection and security

Intelligent network traffic analysis for computer intrusion detection

A. O. Suvorovab, V. A. Suvorovac

a Perm National Research Polytechnic University, Perm, Russia
b HSE University, Moscow, Russia
c JSC "Jet Infosystems", Moscow, Russia
Full-text PDF (808 kB) Citations (1)
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.
Keywords: intrusion detection system, artificial neural networks, network attacks, intelligent traffic analysis.
Funding agency Grant number
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
Citation in format AMSBIB
\Bibitem{SuvSuv19}
\by A.~O.~Suvorov, V.~A.~Suvorova
\paper Intelligent network traffic analysis for computer intrusion detection
\jour Artificial Intelligence and Decision Making
\yr 2019
\issue 1
\pages 62--73
\mathnet{http://mi.mathnet.ru/iipr162}
\crossref{https://doi.org/10.14357/20718594190106}
\elib{https://elibrary.ru/item.asp?id=37179704}
Linking options:
  • https://www.mathnet.ru/eng/iipr162
  • https://www.mathnet.ru/eng/iipr/y2019/i1/p62
  • This publication is cited in the following 1 articles:
    Citing articles in Google Scholar: Russian citations, English citations
    Related articles in Google Scholar: Russian articles, English articles
    Artificial Intelligence and Decision Making
    Statistics & downloads:
    Abstract page:10
    Full-text PDF :26
    References:1
     
      Contact us:
     Terms of Use  Registration to the website  Logotypes © Steklov Mathematical Institute RAS, 2024