Drynx: Decentralized, Secure, Verifiable System for Statistical Queries and Machine Learning on Distributed Datasets

@article{Froelicher2020DrynxDS,
  title={Drynx: Decentralized, Secure, Verifiable System for Statistical Queries and Machine Learning on Distributed Datasets},
  author={David Froelicher and J. Troncoso-Pastoriza and J. S. Sousa and J. Hubaux},
  journal={IEEE Transactions on Information Forensics and Security},
  year={2020},
  volume={15},
  pages={3035-3050}
}
Data sharing has become of primary importance in many domains such as big-data analytics, economics and medical research, but remains difficult to achieve when the data are sensitive. In fact, sharing personal information requires individuals’ unconditional consent or is often simply forbidden for privacy and security reasons. In this paper, we propose Drynx, a decentralized system for privacy-conscious statistical analysis on distributed datasets. Drynx relies on a set of computing nodes to… Expand
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