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
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Ghazi, Badih ; Kumar, Ravi ; Manurangsi, Pasin ; Nelson, Jelani ; Zhou, Samson

Differentially Private Aggregation via Imperfect Shuffling

LIPIcs-ITC-2023-17.pdf (0.7 MB)


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

  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 =		{},
  URN =		{urn:nbn:de:0030-drops-183453},
  doi =		{10.4230/LIPIcs.ITC.2023.17},
  annote =	{Keywords: Differential privacy, private summation, shuffle model}

Keywords: Differential privacy, private summation, shuffle model
Collection: 4th Conference on Information-Theoretic Cryptography (ITC 2023)
Issue Date: 2023
Date of publication: 21.07.2023

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