3 papers
cs.LG2026
Breaking Adversarial Transferability in Fine-Tuned Speech Recognition
Mojtaba Nafez, Aref Mousavi, Mohammad Ebrahim Mahdavi +3
Many organizations fine-tune publicly available pretrained Automatic Speech Recognition (ASR) models and deploy them in black-box settings, assuming limited access provides protect…
eess.AS2026
GhostWord: A Fine-Grained Backdoor Attack on Automatic Speech Recognition
Mojtaba Nafez, Mobina Poulaei, Kiarash Kiani Feriz +4
Automatic Speech Recognition (ASR) systems are widely deployed in safety-critical settings but remain vulnerable to data-poisoning backdoor attacks. Existing ASR backdoors typicall…
cs.LG2025
FrameShield: Adversarially Robust Video Anomaly Detection
Mojtaba Nafez, Mobina Poulaei, Nikan Vasei +3
Weakly Supervised Video Anomaly Detection (WSVAD) has achieved notable advancements, yet existing models remain vulnerable to adversarial attacks, limiting their reliability. Due t…