• DocumentCode
    2019373
  • Title

    Can we beat legitimate cyber behavior mimicking attacks from botnets?

  • Author

    Yu, Shui ; Guo, Song ; Stojmenovic, Ivan

  • Author_Institution
    SIT, Deakin Univ., Melbourne, VIC, Australia
  • fYear
    2012
  • fDate
    25-30 March 2012
  • Firstpage
    2851
  • Lastpage
    2855
  • Abstract
    Botnets are the engine for malicious activities in cyber space. In order to sustain their botnets and disguise their illegal actions, botnet owners are exhausting their strength to mimic legitimate cyber behavior to fly under the radar, e.g. flash crowd mimicking attacks on popular websites. It is an open and challenging problem: can we beat mimicking attacks or not? We use web browsing on popular websites as an example to explore the issue. In our previous work, we discovered that it is almost impossible to detect mimicking attacks from statistics if the number of active bots of a botnet is sufficient (no less than the number of active legitimate users). In this paper, we pointed out that it is usually hard for botnet owners to have sufficient number of active bots in practice. Therefore, we can discriminate mimicking attacks when the sufficient number condition is not met. We prove our claim theoretically and confirm it with simulations. Our findings can also be applied to a large number of other detection related cases.
  • Keywords
    Web sites; information retrieval; online front-ends; security of data; Web browsing; Web sites; active bots; botnets; cyber space; flash crowd mimicking attacks; illegal actions; legitimate cyber behavior; malicious activities; Ash; Browsers; Computer crime; Detection algorithms; Gaussian distribution; Internet; Web pages; botnet; detection; flash crowd attack; mimicking attack;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    INFOCOM, 2012 Proceedings IEEE
  • Conference_Location
    Orlando, FL
  • ISSN
    0743-166X
  • Print_ISBN
    978-1-4673-0773-4
  • Type

    conf

  • DOI
    10.1109/INFCOM.2012.6195714
  • Filename
    6195714