PHISHWEB
Lucas Torrealba Aravena, Javier Bustos-Jiménez, Pedro Casas · 2022
We propose PHISHWEB, a novel approach to website phishing detection, which detects and categorizes malicious websites through a progressive, multi-layered analysis. PHISHWEB combines and extends different detection approaches proposed in the literature, adding robustness to the identification and visibility into the particular type of deception technique employed by the attacker. We present preliminary results on the application of PHISHWEB to multiple open domain-name datasets, showing precision and recall results above 90% for the specific case of lexicographic-based analysis, improving state-of-the-art detection by more than 60% for Domain Generated Algorithms-driven attacks.