Advanced Evasion Attacks and Mitigations on Practical ML-Based Phishing Website Classifiers

Understand

Machine learning (ML) based approaches have been the mainstream solution for anti-phishing detection.

• When they are deployed on the client-side, ML-based classifiers are vulnerable to evasion attacks.
• However, such potential threats have received relatively little attention because existing attacks destruct the functionalities or appearance of webpages and are conducted in the white-box scenario, making it less practical.
• Consequently, it becomes imperative to understand whether it is possible to launch evasion attacks with limited knowledge of the classifier, while preserving the functionalities and appearance.