Rating Web Pages Using Page-Transition Evidence

Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 8233)


The rating of web pages is an important metric that has wide applications, such as web search and malicious page detection. Existing solutions for web page rating rely on either subjective opinions or overall page relationships. In this paper, we present a new solution, SnowEye, to decide the trust rating of web pages with evidence obtained from browsers. The intuition of our approach is that user-activated page transition behaviors provide dynamic evidence to evaluate the rating of web pages. We present an algorithm to rate web pages based on page transitions triggered by users.We prototyped our approach in the Google Chrome browser. Our evaluation through real-world websites and simulation supports our intuition and verifies the correctness of our approach.


Trust Rating Target Page Page Transition Dynamic Evidence Intuitive Requirement 
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  1. 1.
  2. 2.
    Page, L., Brin, S., Motwani, R., Winograd, T.: The pagerank citation ranking: Bringing order to the web. Stanford InfoLab, Technical Report 1999-66 (November 1999)Google Scholar
  3. 3.
    BlockUI, jquery blockui plugin,
  4. 4.
  5. 5.
    Ronda, T., Saroiu, S., Wolman, A.: itrustpage: A user-assisted anti-phishing tool. In: Proceedings of Eurosys 2008. ACM (April 2008)Google Scholar
  6. 6.
  7. 7.
    Camp, L.J.: Net trust: Signaling malicious web sites (2007)Google Scholar
  8. 8.
    Boneh, D.: Spoofguard (2011),
  9. 9.
    Zhang, Y., Hong, J., Cranor, L.: Cantina: A content-based approach to detecting phishing web sites. In: Proceedings of the International World Wide Web Conference (WWW) (May 2007)Google Scholar
  10. 10.
    eBay Inc., ebay toolar (2011),
  11. 11.
    Likarish, P., Jung, E., Dunbar, D., Hansen, T.E., Hourcade, J.P.: B-apt: Bayesian anti-phishing toolbar. In: Proceedings of IEEE International Conference on Communications, ICC 2008. IEEE Press (May 2008)Google Scholar
  12. 12.

Copyright information

© Springer International Publishing Switzerland 2013

Authors and Affiliations

  1. 1.School of Electronic and Information EngineeringBeiHang UniversityChina
  2. 2.School of ComputingNational University of SingaporeSingapore
  3. 3.Institute of Computer Science and TechnologyPeking UniversityChina

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