no code implementations • 11 Dec 2023 • Shangbo Wu, Yu-an Tan, Yajie Wang, Ruinan Ma, Wencong Ma, Yuanzhang Li
To this end, we propose a transferable adversarial attack with fine-grained perturbation optimization in the frequency domain, creating centralized perturbation.
no code implementations • 14 Oct 2023 • Ruinan Ma, Yu-an Tan, Shangbo Wu, Tian Chen, Yajie Wang, Yuanzhang Li
In the first stage, we use an encoder to invisibly write the watermark image into the output images of the original AIGC tool, and reversely extract the watermark image through the corresponding decoder.
no code implementations • 10 Jun 2022 • Nan Luo, Yuanzhang Li, Yajie Wang, Shangbo Wu, Yu-an Tan, Quanxin Zhang
Clean-label settings make the attack more stealthy due to the correct image-label pairs, but some problems still exist: first, traditional methods for poisoning training data are ineffective; second, traditional triggers are not stealthy which are still perceptible.
no code implementations • 13 May 2022 • Shuhao Li, Yajie Wang, Yuanzhang Li, Yu-an Tan
We name our attack \textbf{l-Leaks}.
1 code implementation • 27 Apr 2022 • Huipeng Zhou, Yu-an Tan, Yajie Wang, Haoran Lyu, Shangbo Wu, Yuanzhang Li
We attack the unique self-attention mechanism in ViTs by restructuring the embedded patches of the input.