Combating False Sense of Security: Breaking the Defense of Adversarial Training Via Non-Gradient Adversarial Attack. - Mingyuan Fan 003; Yang Liu 118; Cen Chen 001; Shengxing Yu; Wenzhong Guo; Ximeng Liu (ICASSP, 2022)

SecMPNN: 3-Party Privacy-Preserving Molecular Structure Properties Inference. - Xinying Liao; Jiaye Xue; Shengxing Yu; Ximeng Liu; Jiangang Shu (ICASSP, 2022)

Enhance transferability of adversarial examples with model architecture. - Mingyuan Fan 003; Wenzhong Guo; Shengxing Yu; Zuobin Ying; Ximeng Liu (CoRR, 2022)

Toward Evaluating the Reliability of Deep-Neural-Network-Based IoT Devices. - Mingyuan Fan 003; Yang Liu 118; Cen Chen 001; Shengxing Yu; Wenzhong Guo; Li Wang 056; Ximeng Liu (IEEE Internet Things J., 2022)

FedCML: Federated Clustering Mutual Learning with non-IID Data. - Zekai Chen; Fuyi Wang; Shengxing Yu; Ximeng Liu; Zhiwei Zheng (Euro-Par, 2023)

Lightweight Privacy-Preserving Cross-Cluster Federated Learning With Heterogeneous Data. - Zekai Chen; Shengxing Yu; Farong Chen; Fuyi Wang; Ximeng Liu; Robert H. Deng (IEEE Trans. Inf. Forensics Secur., 2024)

Privacy-Enhancing and Robust Backdoor Defense for Federated Learning on Heterogeneous Data. - Zekai Chen; Shengxing Yu; Mingyuan Fan 003; Ximeng Liu; Robert H. Deng (IEEE Trans. Inf. Forensics Secur., 2024)