most citedAre Diffusion Models Vulnerable to Membership Inference Attacks?

12 citations · 25 across the 5 of their papers we have counts for

collaborators

5 papers

cs.CV20231 cited

RBFormer: Improve Adversarial Robustness of Transformer by Robust Bias

Hao Cheng, Jinhao Duan, Hui Li +6

Recently, there has been a surge of interest and attention in Transformer-based structures, such as Vision Transformer (ViT) and Vision Multilayer Perceptron (VMLP). Compared with…

cs.CV20231 cited

Semantic Adversarial Attacks via Diffusion Models

Chenan Wang, Jinhao Duan, Chaowei Xiao +3

Traditional adversarial attacks concentrate on manipulating clean examples in the pixel space by adding adversarial perturbations. By contrast, semantic adversarial attacks focus o…

cs.CV202311 cited

Exposing the Fake: Effective Diffusion-Generated Images Detection

Ruipeng Ma, Jinhao Duan, Fei Kong +2

Image synthesis has seen significant advancements with the advent of diffusion-based generative models like Denoising Diffusion Probabilistic Models (DDPM) and text-to-image diffus…

cs.CV2023

Improve Video Representation with Temporal Adversarial Augmentation

Jinhao Duan, Quanfu Fan, Hao Cheng +2

Recent works reveal that adversarial augmentation benefits the generalization of neural networks (NNs) if used in an appropriate manner. In this paper, we introduce Temporal Advers…

cs.CV202312 cited

Are Diffusion Models Vulnerable to Membership Inference Attacks?

Jinhao Duan, Fei Kong, Shiqi Wang +2

Diffusion-based generative models have shown great potential for image synthesis, but there is a lack of research on the security and privacy risks they may pose. In this paper, we…