- Unleash the Power of Ellipsis: Accuracy-Enhanced Sparse Vector Technique with Exponential Noise
Yuhan Liu*, Sheng Wang, Yixuan Liu, Feifei Li, Hong Chen
[VLDB 2025] - Sub-optimal Learning in Meta-Classifier Attacks: A Study of Membership Inference on Differentially Private Location Aggregates.
Yuhan Liu*, Florent Guipen, Igor Shilov, Yves-Alexandre De MontJoye
[ArXiv 2024] - Enhanced Privacy Bound For Shuffle Model with Personalized Privacy.
Yixuan Liu, Yuhan Liu*, Li Xiong, Yujie Gu, Hong Chen
[CIKM 2024] - DPDR: Gradient Decomposition and Reconstruction for Differentially Private Deep Learning
Yixuan Liu, Li Xiong, Yuhan Liu*, Yujie Gu, Ruixuan Liu, Hong Chen
[arXiv 2024] - Edge-Protected Triangle Count Estimation under Relationship Local Differential Privacy
Yuhan Liu*, Tianhao Wang, Yixuan Liu, Hong Chen, Cuiping Li
[TKDE 2024] - Echo of Neighbors: Privacy Amplification for Personalized Private Federated Learning with Shuffle Modl
Yixuan Liu, Suyun Zhao, Li Xiong, Yuhan Liu*, Hong Chen
[AAAI 2023] - Collecting Triangle Counts with Edge Relationship Local Differential Privacy
Yuhan Liu*, Suyun Zhao, Yixuan Liu, Dan Zhao, Hong Chen, Cuiping Li
[ICDE 2022] - Privacy-Preserving Techqiues in Federated Leraning (in Chinese)
Yixuan Liu, Hong Chen, Yuhan Liu*, Cuiping Li
[JoS 2022] - State-of-the-Art Privacy Attacks and Defenses on Graphs (in Chinese)
Yuhan Liu*, Hong Chen, Yixuan Liu, Dan Zhao, Cuiping Li
[JoC 2022]
