Abstract
This is a study that focuses on enhancing the mitigation of bulk phishing email messages (i.e. email messages with generic socially engineered content that target a broad range of recipients). This study is based on a phishing website detection technique that we have proposed previously. The previously proposed technique was able to achieve 97% of classification accuracy of phishing websites by lexically analyzing their URLs. The centre claim of this study is that the classification accuracy of anti-phishing email filters enhance when they incorporate the proposed lexical URL analysis technique. To evaluate the claims, a highly accurate anti-phishing email classifier is constructed and tested against publicly available phishing and legitimate email data sets.
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