• DocumentCode
    493704
  • Title

    Research on Behavior Statistic Based Spam Filter

  • Author

    Wang, Meizhen ; Li, Zhitang ; Xiao, Ling ; Zhang, Yunhe

  • Author_Institution
    Sch. of Comput. Sci. & Technol., Huazhong Univ. of Sci. & Technol., Wuhan
  • Volume
    2
  • fYear
    2009
  • fDate
    7-8 March 2009
  • Firstpage
    687
  • Lastpage
    691
  • Abstract
    The spread of spam made a lot of interference to Internet users, and wasted network bandwidth. Anti-spam technology has been developed to the third-generation technology, behavior recognition technology. Many studies have focused on the detection of abnormal behavior in the period of SMTP conversation. In this paper, userpsilas typical sending behavior mathematical model is concerned. To find the abnormal behavior different from the typical behavior, similarity is computed between behaviors of separate users, or between the same userpsilas behavior in long-time and short-time. Combing the common features of email messages, especially most of spam presence of hyperlink, the URL model is also built. Lastly, by Naive Bayes model, several behavior recognizing models can cooperate to detect spam.
  • Keywords
    Bayes methods; Internet; information filters; statistical analysis; unsolicited e-mail; Internet; Naive Bayes model; SMTP conversation; anti-spam technology; behavior recognition technology; behavior statistic-based spam filter; third-generation technology; users typical sending behavior mathematical model; Computer science; Educational technology; Electronic mail; Information filtering; Information filters; Mathematical model; Statistical analysis; Statistics; Uniform resource locators; Unsolicited electronic mail; behavior recognition; histogram distance; spam filter;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Education Technology and Computer Science, 2009. ETCS '09. First International Workshop on
  • Conference_Location
    Wuhan, Hubei
  • Print_ISBN
    978-1-4244-3581-4
  • Type

    conf

  • DOI
    10.1109/ETCS.2009.413
  • Filename
    4959128