• DocumentCode
    1619079
  • Title

    B-APT: Bayesian Anti-Phishing Toolbar

  • Author

    Likarish, Peter ; Jung, Eunjin EJ ; Dunbar, Don ; Hansen, Thomas E. ; Hourcade, Juan Pablo

  • Author_Institution
    Dept of Comput. Sci., Univ. of Iowa, Iowa City, IA
  • fYear
    2008
  • Firstpage
    1745
  • Lastpage
    1749
  • Abstract
    Identity theft is one of the fastest growing crimes in the nation, and phishing has been a primary tool used for this type of theft. In this paper, we present B-APT, a Bayesian anti-phishing toolbar designed to help users identify phishing Websites and protect their sensitive information. Bayesian filters have shown great performance in content-based spam filtering and we adapt a Bayesian filter to detect phishing attacks in the Web browser. The experimental results show that our toolbar effectively detects phishing sites, and is also efficient in terms of page load delay. Among the phishing sites in our testbed, B-APT detected 100% of phishing sites while IE and Firefox only detected 64% and 55%, respectively. Netcraft and SpoofGuard show better accuracy, 98% and 90%, respectively.
  • Keywords
    Bayes methods; Internet; computer crime; filtering theory; online front-ends; unsolicited e-mail; Bayesian anti-phishing toolbar; Bayesian filters; Firefox; IE; Netcraft; SpoofGuard; Web browser; content-based spam filtering; crimes; phishing Web sites; sensitive information protection; theft identification; Bayesian methods; Cities and towns; Computer science; Delay effects; Information filtering; Information filters; Internet; Protection; Testing; Uniform resource locators;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Communications, 2008. ICC '08. IEEE International Conference on
  • Conference_Location
    Beijing
  • Print_ISBN
    978-1-4244-2075-9
  • Electronic_ISBN
    978-1-4244-2075-9
  • Type

    conf

  • DOI
    10.1109/ICC.2008.335
  • Filename
    4533371