• DocumentCode
    2532586
  • Title

    GoldPhish: Using Images for Content-Based Phishing Analysis

  • Author

    Dunlop, Matthew ; Groat, Stephen ; Shelly, David

  • Author_Institution
    Virginia Polytech. Inst. & State Univ., Blacksburg, VA, USA
  • fYear
    2010
  • fDate
    9-15 May 2010
  • Firstpage
    123
  • Lastpage
    128
  • Abstract
    Phishing attacks continue to plague users as attackers develop new ways to fool users into submitting personal information to fraudulent sites. Many schemes claim to protect against phishing sites. Unfortunately, most do not protect against zero-day phishing sites. Those schemes that do allege to provide zero-day protection, often incorrectly label both phishing and legitimate sites. We propose a scheme that protects against zero-day phishing attacks with high accuracy. Our approach captures an image of a page, uses optical character recognition to convert the image to text, then leverages the Google PageRank algorithm to help render a decision on the validity of the site. After testing our tool on 100 legitimate sites and 100 phishing sites, we accurately reported 100% of legitimate sites and 98% of phishing sites.
  • Keywords
    computer crime; content-based retrieval; optical character recognition; unsolicited e-mail; GoldPhish; Google PageRank algorithm; content-based phishing analysis; legitimate sites; optical character recognition; zero-day phishing sites; Alzheimer´s disease; Cardiology; Chemical technology; Clinical diagnosis; Control engineering; Control engineering computing; Dementia; Hospitals; Image analysis; System testing; Anti-phishing; OCR; Toolbar; Zero-day;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Internet Monitoring and Protection (ICIMP), 2010 Fifth International Conference on
  • Conference_Location
    Barcelona
  • Print_ISBN
    978-1-4244-6726-6
  • Type

    conf

  • DOI
    10.1109/ICIMP.2010.24
  • Filename
    5476864