• DocumentCode
    2129153
  • Title

    Detection of Hidden Fraudulent URLs within Trusted Sites Using Lexical Features

  • Author

    Sorio, Enrico ; Bartoli, Alberto ; Medvet, Eric

  • Author_Institution
    DIA - Eng. & Archit. Dept., Univ. of Trieste, Trieste, Italy
  • fYear
    2013
  • fDate
    2-6 Sept. 2013
  • Firstpage
    242
  • Lastpage
    247
  • Abstract
    Internet security threats often involve the fraudulent modification of a web site, often with the addition of new pages at URLs where no page should exist. Detecting the existence of such hidden URLs is very difficult because they do not appear during normal navigation and usually are not indexed by search engines. Most importantly, drive-by attacks leading users to hidden URLs, for example for phishing credentials, may fool even tech-savvy users, because such hidden URLs are increasingly hosted within trusted sites, thereby rendering HTTPS authentication ineffective. In this work, we propose an approach for detecting such URLs based only on their lexical features, which allows alerting the user before actually fetching the page. We assess our proposal on a dataset composed of thousands of URLs, with promising results.
  • Keywords
    Internet; Web sites; computer network security; hypermedia; trusted computing; HTTPS authentication rendering; Internet security threat; Web site; fraudulent modification; hidden fraudulent URL detection; lexical feature; trusted site; Feature extraction; Magnetic heads; Servers; Support vector machines; Training; Tuning; Web sites; phishing; web site defacement;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Availability, Reliability and Security (ARES), 2013 Eighth International Conference on
  • Conference_Location
    Regensburg
  • Type

    conf

  • DOI
    10.1109/ARES.2013.31
  • Filename
    6657247