• DocumentCode
    561335
  • Title

    Lexical URL analysis for discriminating phishing and legitimate e-mail messages

  • Author

    Khonji, Mahmoud ; Iraqi, Youssef ; Jones, Andrew

  • Author_Institution
    Comput. Eng., Khalifa Univ., Sharjah, United Arab Emirates
  • fYear
    2011
  • fDate
    11-14 Dec. 2011
  • Firstpage
    422
  • Lastpage
    427
  • Abstract
    Phishing emails contain socially engineered messages to lure victims into performing certain actions, such as clicking on a URL where a phishing website is hosted, or executing a malware code. In a previous study, we proposed a lexical URL analysis approach for detecting phishing websites. In this study, we extend the approach to the phishing email classification domain. The primary motive behind this study is that most phishing email messages contain URLs that point to phishing websites, and lexically analyzing the URLs can enhance the classification accuracy of email messages. As evaluated in this study, the addition of URL lexical analysis in phishing email classification is effective and results in a highly accurate anti-phishing email classifier.
  • Keywords
    Web sites; computer crime; data analysis; pattern classification; unsolicited e-mail; e-mail message discrimination; legitimate e-mail message; lexical URL analysis approach; malware code; phishing Web site; phishing e-mail message; phishing email classification domain; Accuracy; Electronic mail; Feature extraction; Humans; Performance evaluation; Radio frequency; Training; URLs; emails; lexical analysis; phishing attacks;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Internet Technology and Secured Transactions (ICITST), 2011 International Conference for
  • Conference_Location
    Abu Dhabi
  • Print_ISBN
    978-1-4577-0884-8
  • Type

    conf

  • Filename
    6148476