5 citations · 8 across the 5 of their papers we have counts for
5 papers
Universal Defensive Underpainting Patch: Making Your Text Invisible to Optical Character Recognition
JiaCheng Deng, Li Dong, Jiahao Chen +5
Optical Character Recognition (OCR) enables automatic text extraction from scanned or digitized text images, but it also makes it easy to pirate valuable or sensitive text from the…
Adversarial Privacy Protection on Speech Enhancement
Mingyu Dong, Diqun Yan, Rangding Wang
Speech is easily leaked imperceptibly, such as being recorded by mobile phones in different situations. Private content in speech may be maliciously extracted through speech enhanc…
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…
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…
Adversarial Example Devastation and Detection on Speech Recognition System by Adding Random Noise
Mingyu Dong, Diqun Yan, Yongkang Gong +1
An automatic speech recognition (ASR) system based on a deep neural network is vulnerable to attack by an adversarial example, especially if the command-dependent ASR fails. A defe…