The power of synergy in differential privacy: Combining a small curator with local randomizers

Amos Beimel, Aleksandra Korolova, Kobbi Nissim, Or Sheffet, Uri Stemmer

Research output: Chapter in Book/Report/Conference proceedingConference contribution

5 Scopus citations


Motivated by the desire to bridge the utility gap between local and trusted curator models of differential privacy for practical applications, we initiate the theoretical study of a hybrid model introduced by “Blender” [Avent et al., USENIX Security’17], in which differentially private protocols of n agents that work in the local-model are assisted by a differentially private curator that has access to the data of m additional users. We focus on the regime where m n and study the new capabilities of this (m,n)-hybrid model. We show that, despite the fact that the hybrid model adds no significant new capabilities for the basic task of simple hypothesis-testing, there are many other tasks (under a wide range of parameters) that can be solved in the hybrid model yet cannot be solved either by the curator or by the local-users separately. Moreover, we exhibit additional tasks where at least one round of interaction between the curator and the local-users is necessary – namely, no hybrid model protocol without such interaction can solve these tasks. Taken together, our results show that the combination of the local model with a small curator can become part of a promising toolkit for designing and implementing differential privacy.

Original languageEnglish (US)
Title of host publication1st Conference on Information-Theoretic Cryptography, ITC 2020
EditorsYael Tauman Kalai, Adam D. Smith, Daniel Wichs
PublisherSchloss Dagstuhl- Leibniz-Zentrum fur Informatik GmbH, Dagstuhl Publishing
ISBN (Electronic)9783959771511
StatePublished - Jun 1 2020
Externally publishedYes
Event1st Conference on Information-Theoretic Cryptography, ITC 2020 - Virtual, Boston, United States
Duration: Jun 17 2020Jun 19 2020

Publication series

NameLeibniz International Proceedings in Informatics, LIPIcs
ISSN (Print)1868-8969


Conference1st Conference on Information-Theoretic Cryptography, ITC 2020
Country/TerritoryUnited States
CityVirtual, Boston

All Science Journal Classification (ASJC) codes

  • Software


  • Differential privacy
  • Hybrid model
  • Local model
  • Private learning


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