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Using Domain Top-page Similarity Feature in Machine Learning-Based Web Phishing Detection

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2 Author(s)
Nuttapong Sanglerdsinlapachai ; Thai Comput. Emergency Response Team, Nat. Electron. & Comput. Technol. Center, Pathumthani, Thailand ; Arnon Rungsawang

This paper presents a study on using a concept feature to detect web phishing problem. Following the features introduced in Carnegie Mellon Anti-phishing and Network Analysis Tool (CANTINA), we applied additional domain top-page similarity feature to a machine learning based phishing detection system. We preliminarily experimented with a small set of 200 web data, consisting of 100 phishing webs and another 100 non-phishing webs. The evaluation result in terms of f-measure was up to 0.9250, with 7.50% of error rate.

Published in:

Knowledge Discovery and Data Mining, 2010. WKDD '10. Third International Conference on

Date of Conference:

9-10 Jan. 2010