• DocumentCode
    3177953
  • Title

    Quick traffic classification of BT based on its handshake packets

  • Author

    Li, Hai-cheng ; Li, Ru ; Liu, Qiu-huan

  • Author_Institution
    Coll. of Comput. Sci., Inner Mongolia Univ., Hohhot, China
  • fYear
    2011
  • fDate
    8-10 Aug. 2011
  • Firstpage
    1336
  • Lastpage
    1339
  • Abstract
    With the popularity of the Internet, the extension speed of network resources always lags behind the demands of network bandwidth of network users. It is not an omnipotent solution to increase the available bandwidth. That is why it is important to analyze, control and manage network traffic accurately nowadays. It is reported that, as one of the prominent occupants, peer-to-peer (P2P) traffic takes up at least 70% of the total bandwidth. And BitTorrent (BT) traffic accounts for the first place among all P2P traffic. In an offline analysis on campus traffic captured in our university, we propose a method based on BT handshake packets which can accurately identify and classify BT traffic at a very low cost before evaluating our proposed method with Deep Packet Inspection (DPI) method whose results show that our method needs a much less classification time and storage space which outperforms the DPI-based BT traffic classification.
  • Keywords
    Internet; pattern classification; peer-to-peer computing; BT; BitTorrent traffic; DPI; Internet; P2P; deep packet inspection; handshake packets; network bandwidth; network resources; network users; peer-to-peer traffic; quick traffic classification; Bandwidth; Cryptography; Internet; Payloads; Protocols; Real time systems; Testing; BT handshake packets; BT traffic; traffic classification;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Artificial Intelligence, Management Science and Electronic Commerce (AIMSEC), 2011 2nd International Conference on
  • Conference_Location
    Deng Leng
  • Print_ISBN
    978-1-4577-0535-9
  • Type

    conf

  • DOI
    10.1109/AIMSEC.2011.6010803
  • Filename
    6010803