• DocumentCode
    1768236
  • Title

    Usage of data mining techniques for analyzing network intrusions

  • Author

    Bilalovic, Omar ; Donko, Dzenana

  • Author_Institution
    BH Telecom d.d. Sarajevo, Sarajevo, Bosnia-Herzegovina
  • fYear
    2014
  • fDate
    27-29 Oct. 2014
  • Firstpage
    1
  • Lastpage
    5
  • Abstract
    This paper presents the results of the analysis of the network intrusion detection systems using data mining techniques and anomaly detection. Anomaly detection technique is present for a while in the area of data mining. Previous papers that implement data mining techniques to detect anomaly attacks actually use well-known techniques such as classification or clustering. Anomaly detection technique combines all these techniques. They are also facing problem on the fact that many of the attacks do not have some kind of signature on network and transport layer, so it is not easy to train models for these type of attacks. Network dataset that was used in this paper is DARPA 1998 dataset created in MIT Lincoln Laboratory and is used worldwide for the network testing purposes.
  • Keywords
    data mining; security of data; anomaly detection; data mining technique; network intrusion detection; Algorithm design and analysis; Classification algorithms; Data mining; IP networks; Intrusion detection; Testing; Training; data mining; intrusion detection system; network anomalies;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Telecommunications (BIHTEL), 2014 X International Symposium on
  • Conference_Location
    Sarajevo
  • Print_ISBN
    978-1-4799-8038-3
  • Type

    conf

  • DOI
    10.1109/BIHTEL.2014.6987631
  • Filename
    6987631