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Open Access Publications from the University of California

Verilogo : proactive phishing detection via logo recognition

Abstract

Defending users against fraudulent Web sites (i.e., phishing) is a task that is reactive in practice. Blacklists, spam filters and takedowns all depend on first finding new sites and verifying that they are fraudulent. In this thesis we explore an alternative approach that uses a combination of computer-vision techniques to proactively identify likely phishing pages as they are rendered, interactive queries to validate such pages with brand holders, and a single keyboard-entry filter to minimize false positives. We have developed a prototype version of this approach within the Firefox browser and evaluate it for both accuracy and performance. While no such approach is perfect, we believe our technique offers a significant new capability for minimizing response time in combating a wide range of phishing scams

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