Distributed Differential Privacy By Sampling

@article{Joy2017DistributedDP,
  title={Distributed Differential Privacy By Sampling},
  author={Joshua Joy},
  journal={CoRR},
  year={2017},
  volume={abs/1706.04890}
}
In this paper, we describe our approach to achieve distributed differential privacy by sampling alone. Our mechanism works in the semihonest setting (honest-but-curious whereby aggregators attempt to peek at the data though follow the protocol). We show that the utility remains constant and does not degrade due to the variance as compared to the randomized… CONTINUE READING