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Counteracting Phishing Page Polymorphism: An Image Layout Analysis Approach

  • Ieng-Fat Lam
  • Wei-Cheng Xiao
  • Szu-Chi Wang
  • Kuan-Ta Chen
Part of the Lecture Notes in Computer Science book series (LNCS, volume 5576)

Abstract

Many visual similarity-based phishing page detectors have been developed to detect phishing webpages, however, scammers now create polymorphic phishing pages to breach the defense of those detectors. We call this kind of countermeasure phishing page polymorphism. Polymorphic pages are visually similar to genuine pages they try to mimic, but they use different representation techniques. It increases the level of difficulty to detect phishing pages. In this paper, we propose an effective detection mechanism to detect polymorphic phishing pages. In contrast to existing approaches, we analyze the layout of webpages rather than the HTML codes, colors, or content. Specifically, we compute the similarity degree of a suspect page and an authentic page through image processing techniques. Then, the degrees of similarity are ranked by a classifier trained to detect phishing pages. To verify the efficacy of our phishing detection mechanism, we collected 6,750 phishing pages and 312 mimicked targets for the performance evaluation. The results show that our method achieves an excellent detection rate of 99.6%.

Keywords

False Negative Rate Matched Pair Visual Similarity Page Layout Target Page 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2009

Authors and Affiliations

  • Ieng-Fat Lam
    • 1
  • Wei-Cheng Xiao
    • 1
  • Szu-Chi Wang
    • 2
  • Kuan-Ta Chen
    • 1
  1. 1.Institute of Information ScienceAcademia SinicaTaiwan
  2. 2.Institute of Computer Science and Information EngineeringNational Ilan UniversityTaiwan

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