DocumentCode
1619079
Title
B-APT: Bayesian Anti-Phishing Toolbar
Author
Likarish, Peter ; Jung, Eunjin EJ ; Dunbar, Don ; Hansen, Thomas E. ; Hourcade, Juan Pablo
Author_Institution
Dept of Comput. Sci., Univ. of Iowa, Iowa City, IA
fYear
2008
Firstpage
1745
Lastpage
1749
Abstract
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, B-APT 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.
Keywords
Bayes methods; Internet; computer crime; filtering theory; online front-ends; unsolicited e-mail; Bayesian anti-phishing toolbar; Bayesian filters; Firefox; IE; Netcraft; SpoofGuard; Web browser; content-based spam filtering; crimes; phishing Web sites; sensitive information protection; theft identification; Bayesian methods; Cities and towns; Computer science; Delay effects; Information filtering; Information filters; Internet; Protection; Testing; Uniform resource locators;
fLanguage
English
Publisher
ieee
Conference_Titel
Communications, 2008. ICC '08. IEEE International Conference on
Conference_Location
Beijing
Print_ISBN
978-1-4244-2075-9
Electronic_ISBN
978-1-4244-2075-9
Type
conf
DOI
10.1109/ICC.2008.335
Filename
4533371
Link To Document