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Ing is a plague in cyberspace. Typically, phish detection methods either use humanveri ed URL blacklists or exploit webpage features via machine learning techniques. However, the former is frail in terms of new phish, and the latter su ers from the scarcity of e ective features and the high false positive rate (FP). To alleviate those problems, we propose a layered anti-phishing solution that aims at 1) exploiting the expressiveness of a rich set of features with machine learning to achiev.

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