10 citations · 16 across the 8 of their papers we have counts for
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cs.SD2022
SA: Sliding attack for synthetic speech detection with resistance to clipping and self-splicing
Deng JiaCheng, Dong Li, Yan Diqun +2
Deep neural networks are vulnerable to adversarial examples that mislead models with imperceptible perturbations. In audio, although adversarial examples have achieved incredible a…
cs.CV2022
Detecting and Recovering Adversarial Examples from Extracting Non-robust and Highly Predictive Adversarial Perturbations
Mingyu Dong, Jiahao Chen, Diqun Yan +3
Deep neural networks (DNNs) have been shown to be vulnerable against adversarial examples (AEs) which are maliciously designed to fool target models. The normal examples (NEs) adde…
cs.SD2022★ 1 cited
Transferability of Adversarial Attacks on Synthetic Speech Detection
Jiacheng Deng, Shunyi Chen, Li Dong +2
Synthetic speech detection is one of the most important research problems in audio security. Meanwhile, deep neural networks are vulnerable to adversarial attacks. Therefore, we es…