Privacy-preserving Visualization for Mobile Devices

Introduction

This is the code repository for our EuroVis23 Paper entitled "Privacy-preserving Visualization for Mobile Devices". We propose a perception-driven approach to transform mobile data visualizations into privacy-preserving ones.Specifically,based on human visual perception, we develop a masking scheme to adjust the spatial frequency and luminance contrast of colored visualizations.

You can also check our project webpage for more details.

Citation

If you find our work useful in your research, please consider citing:

@ARTICLE{Zhang2023DontPA,
  title={Don't Peek at My Chart: Privacy-preserving Visualization for Mobile Devices},
  author={Songheng Zhang and Dong Ma and Yong Wang},
  journal={Computer Graphics Forum},
  year={2023},
  volume  = {},
  number  = {},
  pages   = {1-1}
}

Installation

Download the code

$ git clone https://github.com/AlexanderZsh/Privacy-preserving-visualization.git

Code

back_algorithm.py: This script defines the necessary functions to transform a visualization into a privacy-preserving visualization.
example_privacy_preserving_area.ipynb: This notebook provides an example of how to use the functions defined in back_algorithm.py to transform an area-based visual mark into a privacy-preserving visualization.
example_privacy_preserving_line.ipynb: Similarly, this notebook offers an example of applying the functions from back_algorithm.py to transform a line-based visual mark into a privacy-preserving visualization.

Key package

Name	Version
python	3.8.8
numpy	1.21.2
easyocr	1.5.0
opencv	4.5.3
scikit-image	0.18.3
scipy	1.7.1
matplotlib	3.4.3