18 citations · 61 across the 51 of their papers we have counts for
6 papers · 2 filters
Reinforcement Unlearning
Dayong Ye, Tianqing Zhu, Congcong Zhu +6
Machine unlearning refers to the process of mitigating the influence of specific training data on machine learning models based on removal requests from data owners. However, one i…
Boosting Model Inversion Attacks with Adversarial Examples
Shuai Zhou, Tianqing Zhu, Dayong Ye +2
Model inversion attacks involve reconstructing the training data of a target model, which raises serious privacy concerns for machine learning models. However, these attacks, espec…
Machine Unlearning: A Survey
Heng Xu, Tianqing Zhu, Lefeng Zhang +2
Machine learning has attracted widespread attention and evolved into an enabling technology for a wide range of highly successful applications, such as intelligent computer vision,…
Towards Robust GAN-generated Image Detection: a Multi-view Completion Representation
Chi Liu, Tianqing Zhu, Sheng Shen +1
GAN-generated image detection now becomes the first line of defense against the malicious uses of machine-synthesized image manipulations such as deepfakes. Although some existing…
Low-frequency Image Deep Steganography: Manipulate the Frequency Distribution to Hide Secrets with Tenacious Robustness
Huajie Chen, Tianqing Zhu, Yuan Zhao +3
Image deep steganography (IDS) is a technique that utilizes deep learning to embed a secret image invisibly into a cover image to generate a container image. However, the container…
High-frequency Matters: An Overwriting Attack and defense for Image-processing Neural Network Watermarking
Huajie Chen, Tianqing Zhu, Chi Liu +2
In recent years, there has been significant advancement in the field of model watermarking techniques. However, the protection of image-processing neural networks remains a challen…