The Staircase Mechanism in Differential Privacy

Adding Laplacian noise is a standard approach in differential privacy to sanitize numerical data before releasing it. In this paper, we propose an alternative noise adding mechanism: the staircase mechanism, which is a geometric mixture of uniform random variables. The staircase mechanism can replac...

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Veröffentlicht in:IEEE journal of selected topics in signal processing Jg. 9; H. 7; S. 1176 - 1184
Hauptverfasser: Quan Geng, Kairouz, Peter, Sewoong Oh, Viswanath, Pramod
Format: Journal Article
Sprache:Englisch
Veröffentlicht: New York IEEE 01.10.2015
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Schlagworte:
Data privacy
Laplace equations
Noise
Optimization
Privacy
Probability density function
Probability distribution
Random variables
randomized algorithm
Releasing
Sensitivity
Signal processing
Staircases
Two dimensional
ISSN:1932-4553, 1941-0484
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Zusammenfassung:Adding Laplacian noise is a standard approach in differential privacy to sanitize numerical data before releasing it. In this paper, we propose an alternative noise adding mechanism: the staircase mechanism, which is a geometric mixture of uniform random variables. The staircase mechanism can replace the Laplace mechanism in each instance in the literature and for the same level of differential privacy, the performance in each instance improves; the improvement is particularly stark in medium-low privacy regimes. We show that the staircase mechanism is the optimal noise adding mechanism in a universal context, subject to a conjectured technical lemma (which we also prove to be true for one and two dimensional data).
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ISSN:1932-4553
1941-0484
DOI:10.1109/JSTSP.2015.2425831