Identity theft is one of the fastest growing crimes in the nation, and phishing has been a primary tool used for this type of theft. In this paper, we present B-APT, a Bayesian Anti-Phishing Toolbar designed to help users identify phishing websites and protect their sensitive information. Bayesian filters have shown great performance in content-based spam filtering and we adapt a Bayesian filter to detect phishing attacks in the web browser. The experimental results show that our toolbar effectively detects phishing sites, and is also efficient in terms of page load delay. Among the phishing sites in our testbed, BAPT detected 100% of phishing sites while IE and Firefox only detected 64% and 55%, respectively. Netcraft and SpoofGuard show better accuracy, 98% and 90%, respectively. ©2008 IEEE.
CITATION STYLE
Likarish, P., Jung, E., Dunbar, D., Hansen, T. E., & Hourcade, J. P. (2008). B-APT: Bayesian anti-phishing toolbar. In IEEE International Conference on Communications (pp. 1745–1749). https://doi.org/10.1109/ICC.2008.335
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