All Your Fake Detector Are Belong to Us: Evaluating Adversarial Robustness of Fake-news Detectors Under Black-Box Settings H Ali, MS Khan, A AlGhadhban, M Alazmi, A Alzamil, K Al-Utaibi, J Qadir IEEE Access 9, 81678-81692, 2021 | 42 | 2021 |
Tamp-X: Attacking explainable natural language classifiers through tampered activations H Ali, MS Khan, A Al-Fuqaha, J Qadir Computers & Security 120, 102791, 2022 | 13 | 2022 |
Con-detect: Detecting adversarially perturbed natural language inputs to deep classifiers through holistic analysis H Ali, MS Khan, A AlGhadhban, M Alazmi, A Alzamil, K Al-utaibi, J Qadir Computers & Security 132, 103367, 2023 | 6 | 2023 |
Analyzing the robustness of fake-news detectors under black-box adversarial attacks H Ali, MS Khan, A Alghadhban, M Alazmi, A Alzamil, K Al-utaibi, J Qadir IEEE Access, 2021 | 6 | 2021 |