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• W289595871 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" @default.
• W289595871 created "2016-06-24" @default.
• W289595871 creator A5051700680 @default.
• W289595871 date "2010-01-01" @default.
• W289595871 modified "2023-09-23" @default.
• W289595871 title "Verilogo : proactive phishing detection via logo recognition" @default.
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• W289595871 hasPublicationYear "2010" @default.
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