| MHAT: An efficient model-heterogenous aggregation training scheme for federated learning L Hu, H Yan, L Li, Z Pan, X Liu, Z Zhang Information Sciences 560, 493-503, 2021 | 127 | 2021 |
| PPCL: Privacy-preserving collaborative learning for mitigating indirect information leakage H Yan, L Hu, X Xiang, Z Liu, X Yuan Information Sciences 548, 423-437, 2021 | 79 | 2021 |
| Defending against membership inference attacks with high utility by GAN L Hu, J Li, G Lin, S Peng, Z Zhang, Y Zhang, C Dong IEEE Transactions on Dependable and Secure Computing 20 (3), 2144-2157, 2022 | 32 | 2022 |
| Defenses to membership inference attacks: A survey L Hu, A Yan, H Yan, J Li, T Huang, Y Zhang, C Dong, C Yang ACM Computing Surveys 56 (4), 1-34, 2023 | 27 | 2023 |
| Privacy-Preserving Multi-Granular Federated Neural Architecture Search–A General Framework Z Pan, L Hu, W Tang, J Li, Y He, Z Liu IEEE Transactions on Knowledge and Data Engineering 35 (3), 2975-2986, 2021 | 19 | 2021 |
| MTL-leak: Privacy risk assessment in multi-task learning H Yan, A Yan, L Hu, J Liang, H Hu IEEE Transactions on Dependable and Secure Computing 21 (1), 204-215, 2023 | 2 | 2023 |
| Holistic Implicit Factor Evaluation of Model Extraction Attacks A Yan, H Yan, L Hu, X Liu, T Huang IEEE Transactions on Dependable and Secure Computing 20 (6), 4678-4689, 2022 | 2 | 2022 |
| KD‐GAN: An effective membership inference attacks defence framework Z Zhang, G Lin, L Ke, S Peng, L Hu, H Yan International Journal of Intelligent Systems 37 (11), 9921-9935, 2022 | 2 | 2022 |
| VAE-Based Membership Cleanser Against Membership Inference Attacks L Hu, H Yan, Y Peng, H Hu, S Wang, J Li IEEE Transactions on Dependable and Secure Computing, 2024 | | 2024 |
| TFPA: A traceable federated privacy aggregation protocol X Li, Y Long, L Hu, X Tan, J Li World Wide Web 26 (5), 3275-3301, 2023 | | 2023 |
