The Composition Theorem for Differential Privacy

Peter Kairouz, Sewoong Oh, Pramod Viswanath

Research output: Contribution to journalArticlepeer-review

165 Scopus citations

Abstract

Sequential querying of differentially private mechanisms degrades the overall privacy level. In this paper, we answer the fundamental question of characterizing the level of overall privacy degradation as a function of the number of queries and the privacy levels maintained by each privatization mechanism. Our solution is complete: we prove an upper bound on the overall privacy level and construct a sequence of privatization mechanisms that achieves this bound. The key innovation is the introduction of an operational interpretation of differential privacy (involving hypothesis testing) and the use of a data processing inequality along with its converse. Our result improves over the state of the art, and has immediate connections to several problems studied in the literature.

Original languageEnglish (US)
Article number7883827
Pages (from-to)4037-4049
Number of pages13
JournalIEEE Transactions on Information Theory
Volume63
Issue number6
DOIs
StatePublished - Jun 2017
Externally publishedYes

All Science Journal Classification (ASJC) codes

  • Information Systems
  • Computer Science Applications
  • Library and Information Sciences

Keywords

  • Differential privacy
  • hypothesis testing

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