Concentrated Differential Privacy

Preprint English OPEN
Dwork, Cynthia; Rothblum, Guy N.;
(2016)
  • Subject: Computer Science - Data Structures and Algorithms | Computer Science - Cryptography and Security
    acm: ComputingMilieux_COMPUTERSANDSOCIETY | Data_MISCELLANEOUS | ComputingMethodologies_SYMBOLICANDALGEBRAICMANIPULATION

We introduce Concentrated Differential Privacy, a relaxation of Differential Privacy enjoying better accuracy than both pure differential privacy and its popular "(epsilon,delta)" relaxation without compromising on cumulative privacy loss over multiple computations.
  • References (9)

    C. Dwork and J. Lei. Differential privacy and robust statistics. In STOC, 2009.

    [DMNS06] C. Dwork, F. McSherry, K. Nissim, and A. Smith. Calibrating noise to sensitivity in private data analysis. In TCC, pages 265-284, 2006.

    C. Dwork, F. McSherry, and K. Talwar. The price of privacy and the limits of lp decoding. In STOC, pages pp. 85-94, 2007.

    Irit Dinur and Kobbi Nissim. Revealing information while preserving privacy. In PODS, pages 202-210, 2003.

    Cynthia Dwork, Guy N. Rothblum, and Salil P. Vadhan. Boosting and differential privacy. In FOCS, pages 51-60, 2010.

    C. Dwork. Differential privacy. In ICALP, pages 1-12, 2006.

    J. Kahane. Proprits locales des fonctions sries de fourier alatoires. Studia Mathematica, 19(1):1-25, 1960.

    Peter Kairouz, Sewoong Oh, and Pramod Viswanath. The composition theorem for differential privacy. In ICML, pages 1376-1385, 2015.

    Jack Murtagh and Salil P. Vadhan. The complexity of computing the optimal composition of differential privacy. In TCC(A), pages 157-175, 2016.

  • Metrics
Share - Bookmark