FedCTQ

In this paper, we introduce FedCTQ, a novel hierarchical federation-based framework, tailored for contact tracing queries. To bolster the data privacy and security of F-CTQ, we propose a binary-based secret-sharing scheme that ensures robust privacy protection for user trajectory data, while maintaining 100% query accuracy. Concurrently, we address the efficiency of F-CTQ by presenting DistTree, a binary-based distance tree index, enabling real-time and accurate query. Our approach significantly improves F-CTQ performance, achieving a 4.7× to 14.8× speedup compared to competitors, as demonstrated in extensive experiments.

Environment

SecretFlow.version = 1.0.0<br> Python.version = 3.8.17<br> All the experiments are conducted in the federated environment on five nodes, one as a server and the other four as clients, each equipped with two Intel(R) Xeon(R) CPU E5-2650 v4@2.20GHz 12-core processors, 128GB of RAM, and an internet speed of 100MB/s.

Dataset

We give a small dataset of Gowalla for running with 'gowalla_small.csv', while other datasets used can be downloaded in the paper.

Complication

The running example of FedCTQ is as follows:<br> python main.py --dataset Gowalla_Small --patients_num 1 --path 'your_path' --ratio 1.0 --address 'your_address'