Name
Title | ||
|---|---|---|
Visual Similarity Based Anti-phishing with the Combination of Local and Global Features |
Abstract | ||
|---|---|---|
Phishing uses a fake Web page to steal personal sensitive information such as credit card numbers and passwords. Generally, the fake Web page is visually similar to the legitimate target Web page. The phishers can obtain financial benefits through these information. Anti-phishing is very important for a variety of applications such as phishing attacks, online transaction security, and user privacy protection. In this paper, we propose a novel and effective visual similarity based phishing detection approach that compares the snapshot image pair of the suspected Web page and the protected Web page. The proposed approach is based on the key insight that both the local and the global features of the Web page image can be used to represent the visual characteristics of the Web page together. This approach is purely on the image level, and thus can effectively deal with the non-text phishing tricks including images or Flashes objects in the HTML contents. For the local feature, the existence of the target logo is detected. For the global feature, the similarity of the visible part of the Web page is considered. We implemented and evaluated the proposed approach on a large scale dataset consisting of 2,129 real world phishing Web pages and 1,367 irrelevant legitimate Web pages. The experimental results show that the proposed approach can achieve over 90.00% true positive rate and 97.00% true negative rate. Our approach has been applied in the anti-phishing project of a major Internet Service Provider and gives a periodical reports to the potential users. |
Year | DOI | Venue |
|---|---|---|
2014 | 10.1109/TrustCom.2014.28 | TrustCom |
Keywords | Field | DocType |
web sites,global features,internet service provider,html contents,true positive rate,legitimate target web page,local features,emd algorithm,phishing detection, visual similarity, logo detection, emd algorithm,protected web page,computer crime,image level,visual similarity,visual characteristics representation,user privacy protection,snapshot image pair,personal sensitive information stealing,fake web page,true negative rate,passwords,visual similarity antiphishing,feature extraction,suspected web page,credit card numbers,target logo detection,phishing detection,logo detection,nontext phishing tricks,large-scale dataset,web page image,phishing attacks,online transaction security,visual similarity based phishing detection approach,security,visualization,html,web pages,image resolution | Same-origin policy,World Wide Web,Web page,Phishing,Computer science,Tabnabbing,Computer security,Feature extraction,Credit card,Password,Information sensitivity | Conference |
ISSN | Citations | PageRank |
2324-898X | 5 | 0.46 |
References | Authors | |
22 | 5 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Yu Zhou | 1 | 98 | 22.73 |
| Yongzheng Zhang | 2 | 271 | 27.31 |
| Jun Xiao | 3 | 8 | 2.26 |
| Yipeng Wang | 4 | 216 | 25.38 |
| Weiyao Lin | 5 | 732 | 68.05 |