TY  - CONF
ID  - www200958
UR  - http://www2009.eprints.org/58/
A1  - Xiang, Guang
A1  - Hong, Jason I.
Y1  - 2009/04//
N2  - Phishing is a signi?cant 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 speci?c 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%.
TI  - A Hybrid Phish Detection Approach by Identity Discovery and Keywords Retrieval
SP  - 571
M2  - Madrid, Spain
AV  - public
EP  - 571
T2  - 18th International World Wide Web Conference
ER  -