Challenges and approaches for mitigating byzantine attacks in federated learning J Shi, W Wan, S Hu, J Lu, LY Zhang 2022 IEEE International Conference on Trust, Security and Privacy in …, 2022 | 59 | 2022 |
Shielding federated learning: Robust aggregation with adaptive client selection W Wan, S Hu, J Lu, LY Zhang, H Jin, Y He IJCAI 2022, 2022 | 22 | 2022 |
Shielding federated learning: A new attack approach and its defense W Wan, J Lu, S Hu, LY Zhang, X Pei 2021 IEEE Wireless Communications and Networking Conference (WCNC), 1-7, 2021 | 15 | 2021 |
A four-pronged defense against Byzantine attacks in federated learning W Wan, S Hu, M Li, J Lu, L Zhang, LY Zhang, H Jin Proceedings of the 31st ACM International Conference on Multimedia, 7394-7402, 2023 | 9 | 2023 |
Why Does Little Robustness Help? A Further Step Towards Understanding Adversarial Transferability Y Zhang, S Hu, LY Zhang, J Shi, M Li, X Liu, H Jin Proceedings of the 45th IEEE Symposium on Security and Privacy (S&P’24) 2, 2024 | 7* | 2024 |
Shielding Federated Learning: Mitigating Byzantine Attacks with Less Constraints M Li, W Wan, J Lu, S Hu, J Shi, LY Zhang, M Zhou, Y Zheng 2022 18th International Conference on Mobility, Sensing and Networking (MSN …, 2022 | 3 | 2022 |
Misa: Unveiling the vulnerabilities in split federated learning W Wan, Y Ning, S Hu, L Xue, M Li, LY Zhang, H Jin ICASSP 2024-2024 IEEE International Conference on Acoustics, Speech and …, 2024 | 2 | 2024 |
Securely Fine-tuning Pre-trained Encoders Against Adversarial Examples Z Zhou, M Li, W Liu, S Hu, Y Zhang, W Wan, L Xue, LY Zhang, D Yang, ... Proceedings of the 45th IEEE Symposium on Security and Privacy (S&P’24) 3, 2024 | 1 | 2024 |
Depriving the Survival Space of Adversaries Against Poisoned Gradients in Federated Learning J Lu, S Hu, W Wan, M Li, LY Zhang, L Xue, H Wang, H Jin IEEE Transactions on Information Forensics and Security, 2024 | 1 | 2024 |
Preserving Privacy of Input Features Across All Stages of Collaborative Learning J Lu, L Xue, W Wan, M Li, LY Zhang, S Hu 2023 IEEE Intl Conf on Parallel & Distributed Processing with Applications …, 2023 | 1 | 2023 |
DarkFed: A Data-Free Backdoor Attack in Federated Learning M Li, W Wan, Y Ning, S Hu, L Xue, LY Zhang, Y Wang IJCAI 2024, 2024 | | 2024 |
Enhancing Generalization Robustness of Federated Learning in Highly Heterogeneous Environments W Wan, S Hu, J Lu, M Li, Z Zhou, H Jin. SCIENTIA SINICA Informationis, 2024 | | 2024 |