7 citations · 13 across the 6 of their papers we have counts for
6 papers
Revocable Backdoor for Deep Model Trading
Yiran Xu, Nan Zhong, Zhenxing Qian +1
Deep models are being applied in numerous fields and have become a new important digital product. Meanwhile, previous studies have shown that deep models are vulnerable to backdoor…
Object-oriented backdoor attack against image captioning
Meiling Li, Nan Zhong, Xinpeng Zhang +2
Backdoor attack against image classification task has been widely studied and proven to be successful, while there exist little research on the backdoor attack against vision-langu…
Model Copyright Protection in Buyer-seller Environment
Yusheng Guo, Nan Zhong, Zhenxing Qian +1
Training a deep neural network (DNN) requires a high computational cost. Buying models from sellers with a large number of computing resources has become prevailing. However, the b…
PatchCraft: Exploring Texture Patch for Efficient AI-generated Image Detection
Nan Zhong, Yiran Xu, Sheng Li +2
Recent generative models show impressive performance in generating photographic images. Humans can hardly distinguish such incredibly realistic-looking AI-generated images from rea…
Physical Invisible Backdoor Based on Camera Imaging
Yusheng Guo, Nan Zhong, Zhenxing Qian +1
Backdoor attack aims to compromise a model, which returns an adversary-wanted output when a specific trigger pattern appears yet behaves normally for clean inputs. Current backdoor…
Imperceptible Backdoor Attack: From Input Space to Feature Representation
Nan Zhong, Zhenxing Qian, Xinpeng Zhang
Backdoor attacks are rapidly emerging threats to deep neural networks (DNNs). In the backdoor attack scenario, attackers usually implant the backdoor into the target model by manip…