3 papers
cs.CV2024
Intermediate Outputs Are More Sensitive Than You Think
Tao Huang, Qingyu Huang, Jiayang Meng
The increasing reliance on deep computer vision models that process sensitive data has raised significant privacy concerns, particularly regarding the exposure of intermediate resu…
cs.LG2024
Enhancing DP-SGD through Non-monotonous Adaptive Scaling Gradient Weight
Tao Huang, Qingyu Huang, Xin Shi +4
In the domain of deep learning, the challenge of protecting sensitive data while maintaining model utility is significant. Traditional Differential Privacy (DP) techniques such as…
cs.CV2024
Is Diffusion Model Safe? Severe Data Leakage via Gradient-Guided Diffusion Model
Jiayang Meng, Tao Huang, Hong Chen +1
Gradient leakage has been identified as a potential source of privacy breaches in modern image processing systems, where the adversary can completely reconstruct the training image…