• DocumentCode
    153083
  • Title

    User behaviour modelling based DDoS attack detection

  • Author

    Cepheli, Ozge ; Buyukcorak, Saliha ; Kurt, Gunes Karabulut

  • Author_Institution
    Telsiz Haberlesme Arastirma Laboratuvari (THAL), Istanbul Teknik Univ., Istanbul, Turkey
  • fYear
    2014
  • fDate
    23-25 April 2014
  • Firstpage
    2186
  • Lastpage
    2189
  • Abstract
    Distributed Denial of Service (DDoS) attacks are one of the most important threads in network systems. Due to the distributed nature, DDoS attacks are very hard to detect, while they also have the destructive potential of classical denial of service attacks. In this study, a novel 2-step system is proposed for the detection of DDoS attacks. In the first step an anomaly detection is performed on the destination IP traffic. If an anomaly is detected on the network, the system proceeds into the second step where a decision on every user is made due to the behaviour models. Hence, it is possible to detect attacks in the network that diverges from users´ behavior model.
  • Keywords
    IP networks; computer network security; human factors; telecommunication traffic; user modelling; DDoS attack detection; anomaly detection; destination IP traffic; distributed denial of service; network system; user behaviour modelling; Adaptation models; Computer crime; Conferences; IP networks; Mathematical model; Signal processing; DDoS; EM; expectation maximization; user modeling;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Signal Processing and Communications Applications Conference (SIU), 2014 22nd
  • Conference_Location
    Trabzon
  • Type

    conf

  • DOI
    10.1109/SIU.2014.6830697
  • Filename
    6830697