Phishing is a form of online identity theft associated with both social engineering and technical subterfuge. As such, it has become a major threat to information security and personal privacy. According to Gartner Inc., in 2007, more than $3.2 billion was lost due to phishing attacks in the US, and 3.6 million people lost money in such attacks. In this article, we present an effective image-based anti-phishing scheme based on discriminative keypoint features in webpages. We use an invariant content descriptor, the Contrast Context Histogram (CCH), to compute the similarity degree between suspicious pages and authentic pages. The results show that the proposed scheme achieves high accuracy and low error rates.

Kuan-Ta Chen, Jau-Yuan Chen, Chun-Rong Huang, and Chu-Song Chen, "Fighting Phishing with Discriminative Keypoint Features," IEEE Internet Computing, pp. 30--37, May, 2009.

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