Examining the impact of website take-down on phishing
Proceedings of the anti-phishing working groups 2nd annual eCrime researchers summit
Evaluating the Wisdom of Crowds in Assessing Phishing Websites
Financial Cryptography and Data Security
There is no free phish: an analysis of "free" and live phishing kits
WOOT'08 Proceedings of the 2nd conference on USENIX Workshop on offensive technologies
A hybrid phish detection approach by identity discovery and keywords retrieval
Proceedings of the 18th international conference on World wide web
HumanBoost: Utilization of Users' Past Trust Decision for Identifying Fraudulent Websites
ICONIP '09 Proceedings of the 16th International Conference on Neural Information Processing: Part II
An evaluation of machine learning-based methods for detection of phishing sites
ICONIP'08 Proceedings of the 15th international conference on Advances in neuro-information processing - Volume Part I
Intelligent phishing detection system for e-banking using fuzzy data mining
Expert Systems with Applications: An International Journal
A hierarchical adaptive probabilistic approach for zero hour phish detection
ESORICS'10 Proceedings of the 15th European conference on Research in computer 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
Phishing detection with popular search engines: simple and effective
FPS'11 Proceedings of the 4th Canada-France MITACS conference on Foundations and Practice of Security
Trustworthiness testing of phishing websites: A behavior model-based approach
Future Generation Computer Systems
Obtaining the threat model for e-mail phishing
Applied Soft Computing
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Many anti-phishing schemes have recently been proposed in literature. Despite all those efforts, the threat of phishing attacks is not mitigated. One of the main reasons is that phishing attackers have the adaptability to change their tactics with little cost. In this paper, we propose a novel approach, which is independent of any specific phishing implementation. Our idea is to examine the anomalies in web pages, in particular, the discrepancy between a web site's identity and its structural features and HTTP transactions. It demands neither user expertise nor prior knowledge of the website. The evasion of our phishing detection entails high cost to the adversary. As shown by the experiments, our phishing detector functions with low miss rate and low false-positive rate.