• DocumentCode
    3429229
  • Title

    Detection of HTTP-GET flood Attack Based on Analysis of Page Access Behavior

  • Author

    Yatagai, Takeshi ; Isohara, Takamasa ; Sasase, Iwao

  • Author_Institution
    Keio Univ., Yokohama
  • fYear
    2007
  • fDate
    22-24 Aug. 2007
  • Firstpage
    232
  • Lastpage
    235
  • Abstract
    Recently, there are many denial-of-service (DoS) attacks by computer viruses or botnet. DoS attacks to Web services are called HTTP-GET flood attack and threats of them increase day by day. In this type of attacks, malicious clients send a large number of HTTP-GET requests to the target Web server automatically. Since these HTTP-GET requests have legitimate formats and are sent via normal TCP connections, an intrusion detection system (IDS) can not detect them. In this paper, we propose HTTP-GET flood detection techniques based on analysis of page access behavior. We propose two detection algorithms, one is focusing on a browsing order of pages and the other is focusing on a correlation with browsing time to page information size. We implement detection techniques and evaluate attack detection rates, i.e., false positive and false negative. The results show that our techniques can detect the HTTP-GET flood attack effectively.
  • Keywords
    Web services; computer viruses; file servers; hypermedia; telecommunication security; transport protocols; HTTP-GET flood detection technique; Web service; computer virus; denial-of-service attack; page access behavior; Computer crime; Detection algorithms; Distributed computing; Floods; Information analysis; Internet; Intrusion detection; Protocols; Web server; Web services;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Communications, Computers and Signal Processing, 2007. PacRim 2007. IEEE Pacific Rim Conference on
  • Conference_Location
    Victoria, BC
  • Print_ISBN
    978-1-4244-1189-4
  • Electronic_ISBN
    1-4244-1190-4
  • Type

    conf

  • DOI
    10.1109/PACRIM.2007.4313218
  • Filename
    4313218