Robustness and interpretability of phishing detectors under generative AI shifts

This research examines how phishing detectors (AI systems trained to identify fraudulent emails and messages) perform when they encounter new types of attacks generated by generative AI (AI models that create text and content). The study looks at whether these detectors remain reliable and whether humans can understand how they make their decisions when facing AI-generated phishing attempts that differ from their training data.