AdvHash: Set-to-set Targeted Attack on Deep Hashing with One Single Adversarial Patch. - Shengshan Hu; Yechao Zhang; Xiaogeng Liu; Leo Yu Zhang; Minghui Li; Hai Jin 001 (ACM Multimedia, 2021)

Protecting Facial Privacy: Generating Adversarial Identity Masks via Style-robust Makeup Transfer. - Shengshan Hu; Xiaogeng Liu; Yechao Zhang; Minghui Li; Leo Yu Zhang; Hai Jin 001; Libing Wu (CVPR, 2022)

BadHash: Invisible Backdoor Attacks against Deep Hashing with Clean Label. - Shengshan Hu; Ziqi Zhou 001; Yechao Zhang; Leo Yu Zhang; Yifeng Zheng; Yuanyuan He 002; Hai Jin 001 (ACM Multimedia, 2022)

Towards Efficient Data-Centric Robust Machine Learning with Noise-based Augmentation. - Xiaogeng Liu; Haoyu Wang; Yechao Zhang; Fangzhou Wu; Shengshan Hu (CoRR, 2022)

PointCRT: Detecting Backdoor in 3D Point Cloud via Corruption Robustness. - Shengshan Hu; Wei Liu 004; Minghui Li; Yechao Zhang; Xiaogeng Liu; Xianlong Wang 001; Leo Yu Zhang; Junhui Hou (ACM Multimedia, 2023)

AdvCLIP: Downstream-agnostic Adversarial Examples in Multimodal Contrastive Learning. - Ziqi Zhou 001; Shengshan Hu; Minghui Li; Hangtao Zhang; Yechao Zhang; Hai Jin 001 (ACM Multimedia, 2023)

Why Does Little Robustness Help? Understanding Adversarial Transferability From Surrogate Training. - Yechao Zhang; Shengshan Hu; Leo Yu Zhang; Junyu Shi; Minghui Li; Xiaogeng Liu; Wei Wan; Hai Jin 001 (CoRR, 2023)

ECLIPSE: Expunging Clean-Label Indiscriminate Poisons via Sparse Diffusion Purification. - Xianlong Wang 001; Shengshan Hu; Yechao Zhang; Ziqi Zhou 001; Leo Yu Zhang; Peng Xu 003; Wei Wan; Hai Jin 001 (ESORICS (1), 2024)

Unlearnable 3D Point Clouds: Class-wise Transformation Is All You Need. - Xianlong Wang 001; Minghui Li; Wei Liu 004; Hangtao Zhang; Shengshan Hu; Yechao Zhang; Ziqi Zhou 001; Hai Jin 001 (NeurIPS, 2024)

Robust Backdoor Detection for Deep Learning via Topological Evolution Dynamics. - Xiaoxing Mo; Yechao Zhang; Leo Yu Zhang; Wei Luo 001; Nan Sun 002; Shengshan Hu; Shang Gao 003; Yang Xiang 001 (SP, 2024)

Why Does Little Robustness Help? A Further Step Towards Understanding Adversarial Transferability. - Yechao Zhang; Shengshan Hu; Leo Yu Zhang; Junyu Shi; Minghui Li; Xiaogeng Liu; Wei Wan; Hai Jin 001 (SP, 2024)

Securely Fine-tuning Pre-trained Encoders Against Adversarial Examples. - Ziqi Zhou 001; Minghui Li; Wei Liu 004; Shengshan Hu; Yechao Zhang; Wei Wan; Lulu Xue; Leo Yu Zhang; Dezhong Yao 002; Hai Jin 001 (SP, 2024)

Improving Generalization of Universal Adversarial Perturbation via Dynamic Maximin Optimization. - Yechao Zhang; Yingzhe Xu; Junyu Shi; Leo Yu Zhang; Shengshan Hu; Minghui Li; Yanjun Zhang (AAAI, 2025)

Secure Transfer Learning: Training Clean Model Against Backdoor in Pre-Trained Encoder and Downstream Dataset. - Yechao Zhang; Yuxuan Zhou; Tianyu Li; Minghui Li; Shengshan Hu; Wei Luo 001; Leo Yu Zhang (SP, 2025)

Secure Transfer Learning: Training Clean Models Against Backdoor in (Both) Pre-trained Encoders and Downstream Datasets. - Yechao Zhang; Yuxuan Zhou; Tianyu Li; Minghui Li; Shengshan Hu; Wei Luo 001; Leo Yu Zhang (CoRR, 2025)

Spa-VLM: Stealthy Poisoning Attacks on RAG-based VLM. - Lei Yu; Yechao Zhang; Ziqi Zhou 001; Yang Wu; Wei Wan; Minghui Li; Shengshan Hu; Pei Xiaobing; Jing Wang (CoRR, 2025)

Say What You Mean: Natural Language Access Control with Large Language Models for Internet of Things. - Ye Cheng; Mingliang Xu 001; Yue Zhang 025; Kun Li 026; Hao Wu 067; Yechao Zhang; Shaoyong Guo; Wangjie Qiu; Dongxiao Yu; Xiuzhen Cheng 001 (CoRR, 2025)