• DocumentCode
    2732436
  • Title

    Learn to Detect Phishing Scams Using Learning and Ensemble ?Methods

  • Author

    Saberi, Alireza ; Vahidi, Mojtaba ; Bidgoli, Behrouz Minaei

  • Author_Institution
    Iran Univ. of Sci. & Technol., Tehran
  • fYear
    2007
  • fDate
    5-12 Nov. 2007
  • Firstpage
    311
  • Lastpage
    314
  • Abstract
    Phishing attack is a kind of identity theft which tries to steal confidential data like on-line bank account information. In a phishing attack scenario, attacker deceives users by a fake email which is called scam. In this paper we employ three different learning methods to detect phishing scams. Then, we use ensemble methods on their results to improve our scam detection mechanism. Experimental results show that the proposed method can detect 94.4% of scam emails correctly, while only 0.08% of legitimate emails are classified as scams.
  • Keywords
    computer crime; confidential data; ensemble methods; fake email; identity theft; learning; phishing scams; Computer crime; Conferences; Data engineering; Data mining; Electronic mail; Intelligent agent; Internet; Learning systems; Uniform resource locators; Unsolicited electronic mail; Lerning MethodsPhishingScamSpam.;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Web Intelligence and Intelligent Agent Technology Workshops, 2007 IEEE/WIC/ACM International Conferences on
  • Conference_Location
    Silicon Valley, CA
  • Print_ISBN
    0-7695-3028-1
  • Type

    conf

  • DOI
    10.1109/WI-IATW.2007.79
  • Filename
    4427596