Yuting Liang and Ke Yi. 2023. Concentrated Geo-Privacy. In Proceedings of the 2023 ACM SIGSAC Conference on Computer and Communications Security (CCS ’23)
The algorithms and tests were implemented in Python (v3.10).
The following packages can be installed via conda or pip. The specific versions used in the reported experiments are:
numpy v1.24.3
scipy v1.10.1
shapely v2.0.1
To reproduce the results in a specific figure, run its corresponding script listed below.
| File name | Corresponding figure |
|---|---|
| test_traj_rho.py | Figure 2(a),(b). |
| test_traj_m.py | Figure 2(c),(d). |
| test_kpnn_rho.py | Figure 3. |
| test_kpnn_m.py | Figure 4. |
| test_convh_rho.py | Figure 5(a). |
| test_convh_m.py | Figure 5(b). |
For example, to run the test in Figure 5(b):
python test_convh_m.py
The dataset in the ./data/ folder is from: CRAWDAD dataset epfl/mobility (v. 2009-02-24). Downloaded from https://crawdad.org/epfl/mobility/20090224. https://doi.org/10.15783/C7J010
All experiments reported in the paper were run on a linux machine with 8 CPUs and 32GB RAM.