Detection of phishing webpages based on visual similarity
WWW '05 Special interest tracks and posters of the 14th international conference on World Wide Web
The battle against phishing: Dynamic Security Skins
SOUPS '05 Proceedings of the 2005 symposium on Usable privacy and security
Protecting Users Against Phishing Attacks with AntiPhish
COMPSAC '05 Proceedings of the 29th Annual International Computer Software and Applications Conference - Volume 01
Image Analysis for Efficient Categorization of Image-based Spam E-mail
ICDAR '05 Proceedings of the Eighth International Conference on Document Analysis and Recognition
Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
Protecting Users against Phishing Attacks
The Computer Journal
Stronger password authentication using browser extensions
SSYM'05 Proceedings of the 14th conference on USENIX Security Symposium - Volume 14
Lexical feature based phishing URL detection using online learning
Proceedings of the 3rd ACM workshop on Artificial intelligence and security
Web phishing detection using classifier ensemble
Proceedings of the 12th International Conference on Information Integration and Web-based Applications & Services
CANTINA+: A Feature-Rich Machine Learning Framework for Detecting Phishing Web Sites
ACM Transactions on Information and System Security (TISSEC)
Proceedings of the Seventh Symposium on Usable Privacy and Security
Using visual website similarity for phishing detection and reporting
CHI '12 Extended Abstracts on Human Factors in Computing Systems
Recording and replaying navigations on AJAX web sites
ICWE'12 Proceedings of the 12th international conference on Web Engineering
An empirical analysis of malicious internet banking software behavior
Proceedings of the 28th Annual ACM Symposium on Applied Computing
PhishCage: reproduction of fraudulent websites in the emulated internet
Proceedings of the 6th International ICST Conference on Simulation Tools and Techniques
PhishSafe: leveraging modern JavaScript API's for transparent and robust protection
Proceedings of the 4th ACM conference on Data and application security and privacy
Hi-index | 0.00 |
Phishing is a form of online fraud that aims to steal a user's sensitive information, such as online banking passwords or credit card numbers. The victim is tricked into entering such information on a web page that is crafted by the attacker so that it mimics a legitimate page. Recent statistics about the increasing number of phishing attacks suggest that this security problem still deserves significant attention. In this paper, we present a novel technique to visually compare a suspected phishing page with the legitimate one. The goal is to determine whether the two pages are suspiciously similar. We identify and consider three page features that play a key role in making a phishing page look similar to a legitimate one. These features are text pieces and their style, images embedded in the page, and the overall visual appearance of the page as rendered by the browser. To verify the feasibility of our approach, we performed an experimental evaluation using a dataset composed of 41 real-world phishing pages, along with their corresponding legitimate targets. Our experimental results are satisfactory in terms of false positives and false negatives.