The Art of Computer Virus Research and Defense
The Art of Computer Virus Research and Defense
A convenient method for securely managing passwords
WWW '05 Proceedings of the 14th international conference on World Wide Web
Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
An Antiphishing Strategy Based on Visual Similarity Assessment
IEEE Internet Computing
Detecting Phishing Web Pages with Visual Similarity Assessment Based on Earth Mover's Distance (EMD)
IEEE Transactions on Dependable and Secure Computing
Cantina: a content-based approach to detecting phishing web sites
Proceedings of the 16th international conference on World Wide Web
Protection AgainstWeb-based Password Phishing
ITNG '07 Proceedings of the International Conference on Information Technology
Fighting Phishing with Discriminative Keypoint Features
IEEE Internet Computing
A quantitative approach to estimate a website security risk using whitelist
Security and Communication Networks
| Hi-index | 0.00 |
Many visual similarity-based phishing page detectors have been developed to detect phishing webpages, however, scammers now create polymorphic phishing pages to breach the defense of those detectors. We call this kind of countermeasure phishing page polymorphism . Polymorphic pages are visually similar to genuine pages they try to mimic, but they use different representation techniques. It increases the level of difficulty to detect phishing pages. In this paper, we propose an effective detection mechanism to detect polymorphic phishing pages. In contrast to existing approaches, we analyze the layout of webpages rather than the HTML codes, colors, or content. Specifically, we compute the similarity degree of a suspect page and an authentic page through image processing techniques. Then, the degrees of similarity are ranked by a classifier trained to detect phishing pages. To verify the efficacy of our phishing detection mechanism, we collected 6,750 phishing pages and 312 mimicked targets for the performance evaluation. The results show that our method achieves an excellent detection rate of 99.6%.