• DocumentCode
    1949653
  • Title

    ARIMA Based Network Anomaly Detection

  • Author

    Yaacob, Asrul H. ; Tan, Ian K T ; Chien, Su Fong ; Tan, Hon Khi

  • Author_Institution
    FIST, Multimedia Univ., Cyberjaya, Malaysia
  • fYear
    2010
  • fDate
    26-28 Feb. 2010
  • Firstpage
    205
  • Lastpage
    209
  • Abstract
    An early warning system on potential attacks from networks will enable network administrators or even automated network management software to take preventive measures. This is needed as we move towards maximizing the utilization of the network with new paradigms such as Web Services and Software As A Service. This paper introduces a novel approach through using Auto-Regressive Integrated Moving Average (ARIMA) technique to detect potential attacks that may occur in the network. The solution is able to provide feedback through its predictive capabilities and hence provide an early warning system. With the affirmative results, this technique can serve beyond the detection of Denial of Service (DoS) and with sufficient development; an automated defensive solution can be achieved.
  • Keywords
    Web services; autoregressive moving average processes; computer network security; ARIMA based network anomaly detection; Web service; automated defensive solution; automated network management software; autoregressive integrated moving average technique; denial of service; early warning system; potential attacks detection; software as a service; Alarm systems; Communication system software; Communication system traffic control; Computer crime; Intrusion detection; Multimedia systems; Pattern matching; Physics; Telecommunication traffic; Traffic control; ARIMA; Denial of Service; Forecasting; Intrusion Detection; Network Security;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Communication Software and Networks, 2010. ICCSN '10. Second International Conference on
  • Conference_Location
    Singapore
  • Print_ISBN
    978-1-4244-5726-7
  • Electronic_ISBN
    978-1-4244-5727-4
  • Type

    conf

  • DOI
    10.1109/ICCSN.2010.55
  • Filename
    5437603