SHAP-guided adaptive feature weighting for phishing URL detection with a federated learning extension
Abstract Machine-learning phishing URL detectors routinely report accuracies above 97%, yet four weaknesses undermine these results: absent statistical testing, unfair latency benchmarking, uninterpretable predictions, and an inability to use data held privately across organisations. We address all four on the Hannouss...