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GraPhish: A graph-based approach for phishing detection from encrypted TLS traffic
(Elsevier Ltd, 2025) Manguli, K.; Kondaiah, C.; Pais, A.R.; Rao, R.S.
Phishing has increased substantially over the last few years, with cybercriminals deceiving users via spurious websites or confusing mails to steal confidential data like username and password. Even with browser-integrated security indicators like HTTPS prefixes and padlock symbols, new phishing strategies have circumvented these security features. This paper proposes GraPhish, a novel graph-based phishing detection framework that leverages encrypted TLS traffic features. We constructed an in-house dataset and proposed an effective method for graph generation based solely on TLS-based features. Our model performs better than traditional machine learning algorithms. GraPhish achieved an accuracy of 94.82%, a precision of 96.28%, a recall of 92.11%, and an improved AUC-ROC score of 98.29%. © 2025 Elsevier Ltd