Reliability and Robustness analysis of Machine Learning based Phishing URL Detectors. (arXiv:2005.08454v3 [cs.CR] UPDATED)

ML-based Phishing URL (MLPU) detectors serve as the first level of defence to
protect users and organisations from being victims of phishing attacks. Lately,
few studies have launched successful adversarial attacks against specific MLPU
detectors raising questions about their practical reliability and usage.
Nevertheless, the robustness of these systems has not been extensively
investigated. Therefore, the security vulnerabilities of these systems, in
general, remain primarily unknown which calls for testing the robustness of
these systems. In this article, we have …

analysis machine machine learning phishing robustness url