Phishing is a means of obtaining confidential information through fraudulent websites that appear to be legitimate. Anti-phishing detection techniques are either lookup based or classifier based. Lookup based systems suffer from high false negatives while classifier systems suffer from high false positives. To better detect fraudulent websites, we propose in this work an efficient hybrid system that is based on both lookup and a support vector machine classifier that checks features derived from websites URL, text and linkage.
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