Differentially-Private Multi-Party Sketching for Large-Scale Statistics

We consider a scenario where multiple organizations holding large amounts of sensitive data from their users wish to compute aggregate statistics on this data while protecting the privacy of individual users. To support large-scale analytics we investigate how this privacy can be provided for the ca...

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Bibliographic Details

Published in:	Proceedings on Privacy Enhancing Technologies Vol. 2020; no. 3; pp. 153 - 174
Main Authors:	Choi, Seung Geol, Dachman-soled, Dana, Kulkarni, Mukul, Yerukhimovich, Arkady
Format:	Journal Article
Language:	English
Published:	Sciendo 01.07.2020
Subjects:	differential privacy secure computation sketching algorithms
ISSN:	2299-0984, 2299-0984
Online Access:	Get full text
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