Jiaqi Zhao

According to our database, Jiaqi Zhao authored at least 14 papers between 2022 and 2025.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2025

COKV: Key-Value Data Collection With Condensed Local Differential Privacy.

Junpeng Zhang, Hui Zhu, Jiaqi Zhao, Rongxing Lu, Yandong Zheng, Jiezhen Tang, Hui Li

IEEE Trans. Inf. Forensics Secur., 2025

SGBoost⁺: Efficient and Privacy-Preserving Vertical Boosting Trees for Federated Outsourced Training and Inference.

Wei Xu, Hui Zhu, Jiaqi Zhao, Yandong Zheng, Fengwei Wang, Baishun Sun, Songnian Zhang, Dengguo Feng

IEEE Trans. Inf. Forensics Secur., 2025

SplitAD: A lightweight and privacy-enhancing vertical federated anomaly detection framework based on hierarchical autoencoders.

Jiaqi Zhao, Hui Zhu, Junpeng Zhang, Jiezhen Tang, Fengwei Wang, Hui Li

Inf. Sci., 2025

2024

Efficient and Privacy-Preserving Federated Learning Against Poisoning Adversaries.

Jiaqi Zhao, Hui Zhu, Fengwei Wang, Yandong Zheng, Rongxing Lu, Hui Li

IEEE Trans. Serv. Comput., 2024

ELXGB: An Efficient and Privacy-Preserving XGBoost for Vertical Federated Learning.

Wei Xu, Hui Zhu, Yandong Zheng, Fengwei Wang, Jiaqi Zhao, Zhe Liu, Hui Li

IEEE Trans. Serv. Comput., 2024

UNIRE: Secure Trajectory-User Linking Model Aggregation with Knowledge Transfer.

Jiezhen Tang, Hui Zhu, Yandong Zheng, Junpeng Zhang, Fengwei Wang, Jiaqi Zhao, Hui Li

Proceedings of the 23rd IEEE International Conference on Trust, 2024

2023

Efficient and privacy-preserving tree-based inference via additive homomorphic encryption.

Jiaqi Zhao, Hui Zhu, Fengwei Wang, Rongxing Lu, Hui Li

Inf. Sci., December, 2023

SGBoost: An Efficient and Privacy-Preserving Vertical Federated Tree Boosting Framework.

Jiaqi Zhao, Hui Zhu, Wei Xu, Fengwei Wang, Rongxing Lu, Hui Li

IEEE Trans. Inf. Forensics Secur., 2023

VFLR: An Efficient and Privacy-Preserving Vertical Federated Framework for Logistic Regression.

Jiaqi Zhao, Hui Zhu, Fengwei Wang, Rongxing Lu, Ermei Wang, Linfeng Li, Hui Li

IEEE Trans. Cloud Comput., 2023

Efficient and Privacy-Preserving Logistic Regression Prediction over Vertically Partitioned Data.

Jiaqi Zhao, Hui Zhu, Fengwei Wang, Rongxing Lu, Hui Li

Proceedings of the IEEE Global Communications Conference, 2023

2022

PVD-FL: A Privacy-Preserving and Verifiable Decentralized Federated Learning Framework.

Jiaqi Zhao, Hui Zhu, Fengwei Wang, Rongxing Lu, Zhe Liu, Hui Li

IEEE Trans. Inf. Forensics Secur., 2022

CORK: A privacy-preserving and lossless federated learning scheme for deep neural network.

Jiaqi Zhao, Hui Zhu, Fengwei Wang, Rongxing Lu, Hui Li, Jingwei Tu, Jie Shen

Inf. Sci., 2022

An Efficient and Privacy-Preserving Route Matching Scheme for Carpooling Services.

Qi Xu, Hui Zhu, Yandong Zheng, Jiaqi Zhao, Rongxing Lu, Hui Li

IEEE Internet Things J., 2022

ACCEL: an efficient and privacy-preserving federated logistic regression scheme over vertically partitioned data.

Jiaqi Zhao, Hui Zhu, Fengwei Wang, Rongxing Lu, Hui Li, Zhongmin Zhou, Haitao Wan

Sci. China Inf. Sci., 2022