scottshufe / HyObscure

The code repository for paper HyObscure.

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HyObscure

Minimizing privacy leakage and ensuring data utility is a critical problem to social media platforms (SMPs) for data publishing, namely privacy preserving data publishing problem. Due to data correlations, it is challenging to achieve an optimal privacy-utility tradeoff with hybrid obscuring on heterogeneous data. HyObscure is a novel hybrid protection mechanism focusing on heterogeneous data publishing on SMPs, which cross-iteratively optimizes the generalization and obfuscation operations to maximize privacy protection under a certain utility guarantee.

Software Environment

  • MATLAB and CVX package with Mosek solver
  • Python3.6. All necessary packages are listed in file requirements.txt.
  • MATLAB Engine API for Python

Python Packages Installation

pip install -r requirements.txt

MATLAB Engine API for Python Installation

See https://www.mathworks.com/help/matlab/matlab_external/install-the-matlab-engine-for-python.html for details.

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The code repository for paper HyObscure.


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