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cs.CR2025
EPSpatial: Achieving Efficient and Private Statistical Analytics of Geospatial Data
Chuan Zhang, Xuhao Ren, Zhangcheng Huang +3
Geospatial data statistics involve the aggregation and analysis of location data to derive the distribution of clients within geospatial. The need for privacy protection in geospat…
cs.CR2022★ 2 cited
A Privacy-Preserving Subgraph-Level Federated Graph Neural Network via Differential Privacy
Yeqing Qiu, Chenyu Huang, Jianzong Wang +2
Currently, the federated graph neural network (GNN) has attracted a lot of attention due to its wide applications in reality without violating the privacy regulations. Among all th…