Corpus ID: 5952553

DPCube: Differentially Private Histogram Release through Multidimensional Partitioning

@article{Xiao2014DPCubeDP,
  title={DPCube: Differentially Private Histogram Release through Multidimensional Partitioning},
  author={Yonghui Xiao and Li Xiong and Liyue Fan and Slawomir Goryczka and Haoran Li},
  journal={ArXiv},
  year={2014},
  volume={abs/1202.5358}
}
Differential privacy is a strong notion for protecting individual privacy in privacy preserving data analysis or publishing. In this paper, we study the problem of differentially private histogram release for random workloads. We study two multidimensional partitioning strategies including: 1) a baseline cell-based partitioning strategy for releasing an equi-width cell histogram, and 2) an innovative 2-phase kd-tree based partitioning strategy for releasing a v-optimal histogram. We formally… Expand
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References

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This paper proposes two multidimensional partitioning strategies including a baseline cell-based partitioning and an innovative kd-tree based partitioning for differentially private histogram release based on an interactive differential privacy interface. Expand
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