Con-Detect: Detecting adversarially perturbed natural language inputs to deep classifiers through holistic analysis.
Comput. Secur., September, 2023
Tamp-X: Attacking explainable natural language classifiers through tampered activations.
Comput. Secur., 2022
All Your Fake Detector are Belong to Us: Evaluating Adversarial Robustness of Fake-News Detectors Under Black-Box Settings.
IEEE Access, 2021