DistilBERT reaches 99.78% accuracy on heterogeneous phishing datasets while CatBoost, CNN, and logistic regression also perform well; XAI methods identify key features and an MCP system enables real-time detection.
Ai meta-learners and extra-trees algorithm for the detection of phishing websites.IEEE Access, 8:142532– 142542
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Explainable Machine Learning for Phishing Detection on Heterogeneous Datasets with MCP-Enabled Deployment
DistilBERT reaches 99.78% accuracy on heterogeneous phishing datasets while CatBoost, CNN, and logistic regression also perform well; XAI methods identify key features and an MCP system enables real-time detection.