License: 
Creative Commons Attribution 4.0 International license (CC BY 4.0)
When quoting this document, please refer to the following
DOI: 10.4230/LIPIcs.ITC.2023.17
URN: urn:nbn:de:0030-drops-183453
URL: http://dagstuhl.sunsite.rwth-aachen.de/volltexte/2023/18345/
Ghazi, Badih ;
Kumar, Ravi ;
Manurangsi, Pasin ;
Nelson, Jelani ;
Zhou, Samson
Differentially Private Aggregation via Imperfect Shuffling
Abstract
In this paper, we introduce the imperfect shuffle differential privacy model, where messages sent from users are shuffled in an almost uniform manner before being observed by a curator for private aggregation. We then consider the private summation problem. We show that the standard split-and-mix protocol by Ishai et. al. [FOCS 2006] can be adapted to achieve near-optimal utility bounds in the imperfect shuffle model. Specifically, we show that surprisingly, there is no additional error overhead necessary in the imperfect shuffle model.
BibTeX - Entry
@InProceedings{ghazi_et_al:LIPIcs.ITC.2023.17,
author = {Ghazi, Badih and Kumar, Ravi and Manurangsi, Pasin and Nelson, Jelani and Zhou, Samson},
title = {{Differentially Private Aggregation via Imperfect Shuffling}},
booktitle = {4th Conference on Information-Theoretic Cryptography (ITC 2023)},
pages = {17:1--17:22},
series = {Leibniz International Proceedings in Informatics (LIPIcs)},
ISBN = {978-3-95977-271-6},
ISSN = {1868-8969},
year = {2023},
volume = {267},
editor = {Chung, Kai-Min},
publisher = {Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
address = {Dagstuhl, Germany},
URL = {https://drops.dagstuhl.de/opus/volltexte/2023/18345},
URN = {urn:nbn:de:0030-drops-183453},
doi = {10.4230/LIPIcs.ITC.2023.17},
annote = {Keywords: Differential privacy, private summation, shuffle model}
}
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Keywords: |
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Differential privacy, private summation, shuffle model |
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Collection: |
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4th Conference on Information-Theoretic Cryptography (ITC 2023) |
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Issue Date: |
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2023 |
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Date of publication: |
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21.07.2023 |
