Name
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. |
Year | DOI | Venue |
|---|---|---|
2008 | 10.1109/ICC.2008.335 | Beijing |
Keywords | Field | DocType |
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 | Phishing,Computer science,Computer security,Identity theft,Testbed,Spoofed URL,Information sensitivity,Bayesian probability,The Internet,Toolbar | Conference |
ISSN | ISBN | Citations |
1550-3607 | 978-1-4244-2075-9 | 17 |
PageRank | References | Authors |
0.82 | 9 | 5 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Peter Likarish | 1 | 92 | 6.86 |
| Eunjin Jung | 2 | 125 | 13.06 |
| Don Dunbar | 3 | 18 | 1.18 |
| Thomas E. Hansen | 4 | 113 | 6.12 |
| Juan Pablo Hourcade | 5 | 821 | 91.31 |