Structure and Sensitivity in Differential Privacy: Comparing K-Norm Mechanisms

@article{Awan2018StructureAS,
  title={Structure and Sensitivity in Differential Privacy: Comparing K-Norm Mechanisms},
  author={Jordan Awan and Aleksandra B. Slavkovic},
  journal={arXiv: Methodology},
  year={2018}
}
  • Jordan Awan, Aleksandra B. Slavkovic
  • Published 2018
  • Mathematics
  • arXiv: Methodology
  • A common way to protect privacy of sensitive information is to introduce additional randomness, beyond sampling. Differential Privacy (DP) provides a rigorous framework for quantifying privacy risk of such procedures which allow for data summary releases, such as a statistic $T$. However in theory and practice, the structure of the statistic $T$ is often not carefully analyzed, resulting in inefficient implementation of DP mechanisms that introduce excessive randomness to minimize the risk… CONTINUE READING

    Figures from this paper.

    Citations

    Publications citing this paper.
    SHOWING 1-10 OF 11 CITATIONS

    Elliptical Perturbations for Differential Privacy

    VIEW 4 EXCERPTS
    CITES BACKGROUND

    KNG: The K-Norm Gradient Mechanism

    Secure and Differentially Private Logistic Regression for Horizontally Distributed Data

    VIEW 1 EXCERPT
    CITES BACKGROUND

    Differentially Private Inference for Binomial Data

    VIEW 4 EXCERPTS
    CITES BACKGROUND & METHODS

    Differentially Private Bayesian Linear Regression

    VIEW 2 EXCERPTS
    CITES METHODS & BACKGROUND

    References

    Publications referenced by this paper.
    SHOWING 1-10 OF 46 REFERENCES

    New Statistical Applications for Differential Privacy

    VIEW 3 EXCERPTS
    HIGHLY INFLUENTIAL

    The Algorithmic Foundations of Differential Privacy

    • C. Dwork, A. Roth
    • Computer Science
    • Foundations and Trends in Theoretical Computer Science
    • 2014

    Differential Privacy as a Mutual Information Constraint

    • Paul W. Cuff, Lanqing Yu
    • Computer Science, Mathematics
    • ACM Conference on Computer and Communications Security
    • 2016
    VIEW 1 EXCERPT