Enhancing Privacy through Unlinkable Data Sharing with User-in-the-Loop Access Control

This repository contains the code and simulation setup for experiments presented in our study on Enhancing Privacy through Unlinkable Data Sharing with User-in-the-Loop Access Control.

Repository Structure

• implementation/
  • simulation.py: Main simulation script.
  • generate_seed.py: Script to generate the Zipf distribution.
  • zipf_50k_seed.json: Pre-generated Zipf distribution file (50,000 users).
  • requirements.txt: Python dependencies.

You can download our simulation results as a compressed archive (~5 GB; ~1.2 million files) here: https://drive.proton.me/urls/GAW8HEDT34#ZHvI5ZpDbBu7

Reproducing Results

1. Prepare the environment

Install Python dependencies:

pip install -r ./implementation/requirements.txt

Install GNU Parallel (if not already installed):

sudo apt-get install parallel

2. Generate Zipf distribution (optional)

You can use the provided Zipf distribution (./implementation/zipf_50k_seed.json), or generate your own with:

python3 ./implementation/generate_seed.py

3. Run simulations

We recommend using GNU Parallel to distribute the workload across multiple CPU cores:

parallel --jobs 80 \
    'python3 ./implementation/simulation.py --seed "./implementation/zipf_50k_seed.json" --q {1} --r {2} --tau {3} --run {4}' \
    ::: $(seq 0.1 0.1 0.9) ::: $(seq 0.1 0.1 0.9) ::: {1..49} ::: {1..100}

Simulation output will be saved under the ./results/ directory.