This report contains code of Protecting participants or population? Comparison of k-anonymous Origin-Destination matrices for 2025 NetMob data challenge
The NetMob25 Dataset: A High-resolution Multi-layered View of Individual Mobility in Greater Paris Region The data is not publicly available. To reproduce our results, you must request access to the dataset from the challenge organizers. See the Data Challenge Website for access instructions and the dataset documentation for more details.
For our experiments and comparisons, we used algorithms provided in the following papers:
- ATG-Soft: Adaptative generalisation over a value hierarchy for the k-anonymisation of Origin–Destination matrices
- Mondrian: Mondrian Multidimensional K-Anonymity
- OIGH: Data privacy preservation algorithm with k-anonymity
We gratefully acknowledge the authors of ATG-Soft for sharing codes.
We use the implementation of Mondrian from this repo
If you use this repository, please make sure to also cite the original works.