SGBoost: An Efficient and Privacy-Preserving Vertical Federated Tree Boosting Framework. - Jiaqi Zhao 005; Hui Zhu 001; Wei Xu 042; Fengwei Wang; Rongxing Lu; Hui Li 006 (IEEE Trans. Inf. Forensics Secur., 2023)

Efficient and Lossless Integrity-preserving Training Scheme for High-dimensional Logistic Regression over Vertical Data. - Wei Xu 042; Hui Zhu 001; Ruikang Liu; Yandong Zheng; Fengwei Wang; Dengguo Feng (GLOBECOM, 2024)

ToNN: An Oblivious Neural Network Prediction Scheme With Semi-Honest TEE. - Wei Xu 042; Hui Zhu 001; Yandong Zheng; Fengwei Wang; Jiafeng Hua; Dengguo Feng; Hui Li 006 (IEEE Trans. Inf. Forensics Secur., 2024)

ELXGB: An Efficient and Privacy-Preserving XGBoost for Vertical Federated Learning. - Wei Xu 042; Hui Zhu 001; Yandong Zheng; Fengwei Wang; Jiaqi Zhao 005; Zhe Liu 001; Hui Li 006 (IEEE Trans. Serv. Comput., 2024)

Enhancing paillier to fully homomorphic encryption with semi-honest TEE. - Yunyi Fang; Xiaopeng Yang; Hui Zhu 001; Wei Xu 042; Yandong Zheng; Xingdong Liu; Dong Zhang (Peer Peer Netw. Appl., 2024)

SGBoost+: Efficient and Privacy-Preserving Vertical Boosting Trees for Federated Outsourced Training and Inference. - Wei Xu 042; Hui Zhu 001; Jiaqi Zhao 005; Yandong Zheng; Fengwei Wang; Baishun Sun; Songnian Zhang; Dengguo Feng (IEEE Trans. Inf. Forensics Secur., 2025)