We have released a package named Multi-Freq-LDPy for Multiple Frequency Estimation Under Local Differential Privacy in Python.
This repository is organized per paper (experiments and protocols) and is regularly updated. Please refer to the papers folder.
differential privacy, local differential privacy, longitudinal studies, multidimensional data, big data privacy, human mobility, privacy-preserving machine learning.
I mainly used Python3 with numpy, pandas, and numba libaries. Although not tested, the codes should run with any recent versions. The versions I use are listed below:
- Python 3.8.8
- Numpy 1.19.5
- Pandas 1.2.4
- Numba 0.53.1
For any questions about the experiments, please contact Héber H. Arcolezi: heber.hwang-arcolezi [at] inria.fr