Adversarial Robustness of Phishing Email Detection: A Comparative Study of TF-IDF + Logistic Regression and Fine-Tuned DistilBERT

Researchers compared TF-IDF + Logistic Regression and fine-tuned DistilBERT for phishing email detection, finding both exceeded 98% accuracy on clean data but dropped to 64.00% and 63.64% under adversarial testing. The models showed similar vulnerability despite relying on different evidence. Adversarial testing revealed partly complementary failure modes.