Unrestricted Adversarial Attacks on ImageNet Competition. - Yuefeng Chen; Xiaofeng Mao; Yuan He 011; Hui Xue 001; Chao Li; Yinpeng Dong; Qi-An Fu; Xiao Yang; Wenzhao Xiang 001; Tianyu Pang; Hang Su 006; Jun Zhu 001; et al. (CoRR, 2021)

Boosting Adversarial Transferability of MLP-Mixer. - Haoran Lyu; Yajie Wang; Yu-an Tan 001; Huipeng Zhou; Yuhang Zhao 003; Quanxin Zhang 001 (CoRR, 2022)

Improving the Transferability of Adversarial Examples with Restructure Embedded Patches. - Huipeng Zhou; Yu-an Tan 001; Yajie Wang; Haoran Lyu; Shangbo Wu; Yuanzhang Li 001 (CoRR, 2022)

Artificial Intelligence Security Competition (AISC). - Yinpeng Dong; Peng Chen; Senyou Deng; Lianji L; Yi Sun; Hanyu Zhao; Jiaxing Li; Yunteng Tan; Xinyu Liu; Yangyi Dong; Enhui Xu; Jincai Xu; et al. (CoRR, 2022)

Modifying the one-hot encoding technique can enhance the adversarial robustness of the visual model for symbol recognition. - Yi Sun; Jun Zheng 007; Hanyu Zhao; Huipeng Zhou; Jiaxing Li; Fan Li; Zehui Xiong; Jun Liu; Yuanzhang Li 001 (Expert Syst. Appl., 2024)

Crafting Transferable Adversarial Examples Against Face Recognition via Gradient Eroding. - Huipeng Zhou; Yajie Wang; Yu-an Tan 001; Shangbo Wu; Yuhang Zhao 003; Quanxin Zhang 001; Yuanzhang Li 001 (IEEE Trans. Artif. Intell., 2024)

Maxwell's Demon in MLP-Mixer: towards transferable adversarial attacks. - Haoran Lyu; Yajie Wang; Yu-An Tan 001; Huipeng Zhou; Yuhang Zhao 003; Quanxin Zhang 001 (Cybersecur., 2024)