The Optimal Noise-Adding Mechanism in Differential Privacy

Differential privacy is a framework to quantify to what extent individual privacy in a statistical database is preserved while releasing useful aggregate information about the database. In this paper, within the classes of mechanisms oblivious of the database and the queriesqueries beyond the global...

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Bibliographic Details
Published in:	IEEE transactions on information theory Vol. 62; no. 2; pp. 925 - 951
Main Authors:	Quan Geng, Viswanath, Pramod
Format:	Journal Article
Language:	English
Published:	New York IEEE 01.02.2016 The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subjects:	Asymptotic properties Context Data privacy Density Information theory Laplace equations Noise Optimization Privacy Probability Probability distribution Queries randomized algorithm Sensitivity Staircases Data privacy randomized algorithm
ISSN:	0018-9448, 1557-9654
Online Access:	Get full text
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