SoK: Privacy-Preserving Collaborative Tree-based Model Learning

@article{Chatel2021SoKPC,
  title={SoK: Privacy-Preserving Collaborative Tree-based Model Learning},
  author={Sylvain Chatel and Apostolos Pyrgelis and Juan Ram{\'o}n Troncoso-Pastoriza and Jean-Pierre Hubaux},
  journal={Proceedings on Privacy Enhancing Technologies},
  year={2021},
  volume={2021},
  pages={182 - 203}
}
Abstract Tree-based models are among the most efficient machine learning techniques for data mining nowadays due to their accuracy, interpretability, and simplicity. The recent orthogonal needs for more data and privacy protection call for collaborative privacy-preserving solutions. In this work, we survey the literature on distributed and privacy-preserving training of tree-based models and we systematize its knowledge based on four axes: the learning algorithm, the collaborative model, the… 
3 Citations

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