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

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

Abstract

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
DOIs
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
Volume163
ISSN (Print)1868-8969

Conference

Conference1st Conference on Information-Theoretic Cryptography, ITC 2020
Country/TerritoryUnited States
CityVirtual, Boston
Period6/17/206/19/20

All Science Journal Classification (ASJC) codes

  • Software

Keywords

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

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