creators_name: Xiang, Guang creators_name: Hong, Jason I. type: conference_item datestamp: 2009-04-06 19:10:09 lastmod: 2009-04-07 14:02:28 metadata_visibility: show title: A Hybrid Phish Detection Approach by Identity Discovery and Keywords Retrieval ispublished: pub full_text_status: public pres_type: paper abstract: Phishing is a significant security threat to the Internet, which causes tremendous economic loss every year. In this paper, we proposed a novel hybrid phish detection method based on information extraction (IE) and information retrieval (IR) techniques. The identity-based component of our method detects phishing webpages by directly discovering the inconsistency between their identity and the identity they are imitating. The keywords-retrieval component utilizes IR algorithms exploiting the power of search engines to identify phish. Our method requires no training data, no prior knowledge of phishing signatures and specific implementations, and thus is able to adapt quickly to constantly appearing new phishing patterns. Comprehensive experiments over a diverse spectrum of data sources with 11449 pages show that both components have a low false positive rate and the stacked approach achieves a true positive rate of 90.06% with a false positive rate of 1.95%. date: 2009-04 pagerange: 571-571 event_title: 18th International World Wide Web Conference event_location: Madrid, Spain event_dates: April 20th-24th, 2009 event_type: conference refereed: TRUE citation: Xiang, Guang and Hong, Jason I. (2009) A Hybrid Phish Detection Approach by Identity Discovery and Keywords Retrieval. In: 18th International World Wide Web Conference, April 20th-24th, 2009, Madrid, Spain. document_url: http://www2009.eprints.org/58/1/p571.pdf