Detecting visually similar Web pages: Application to phishing detection

  • Authors:
  • Teh-Chung Chen;Scott Dick;James Miller

  • Affiliations:
  • University of Alberta, Canada;University of Alberta, Canada;University of Alberta, Canada

  • Venue:
  • ACM Transactions on Internet Technology (TOIT)
  • Year:
  • 2010

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Abstract

We propose a novel approach for detecting visual similarity between two Web pages. The proposed approach applies Gestalt theory and considers a Web page as a single indivisible entity. The concept of supersignals, as a realization of Gestalt principles, supports our contention that Web pages must be treated as indivisible entities. We objectify, and directly compare, these indivisible supersignals using algorithmic complexity theory. We illustrate our approach by applying it to the problem of detecting phishing scams. Via a large-scale, real-world case study, we demonstrate that 1) our approach effectively detects similar Web pages; and 2) it accuractely distinguishes legitimate and phishing pages.