/Differential_Privacy_CPS-main

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Differential_Privacy_CPS

Python implementation of the research paper Leveraging Unique CPS Properties to Design Better Privacy-Enhancing Algorithms https://doi.org/10.1145/3055305.3055313

Attack Using Kalman Filter

Using Kalman Filter tried to estimate both the private consumer data and added noise.

Instructions to run code

  1. Setup virtual environment and install requirements from requirements.txt
  2. Differential privacy code is in differential_privacy.py
  3. Kalman Filter code is in kalman.py
  4. Results are saved in results folder