Bounded-Leakage Differential Privacy

Authors Katrina Ligett, Charlotte Peale, Omer Reingold

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Author Details

Katrina Ligett
  • Computer Science Department, Hebrew University of Jerusalem, Israel
Charlotte Peale
  • Stanford University, Stanford, CA, USA
Omer Reingold
  • Computer Science Department, Stanford University, Stanford, CA, USA


Part of this work was done while the first and third authors were visiting the Simons Institute for the Theory of Computing.

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Katrina Ligett, Charlotte Peale, and Omer Reingold. Bounded-Leakage Differential Privacy. In 1st Symposium on Foundations of Responsible Computing (FORC 2020). Leibniz International Proceedings in Informatics (LIPIcs), Volume 156, pp. 10:1-10:20, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2020)


We introduce and study a relaxation of differential privacy [Dwork et al., 2006] that accounts for mechanisms that leak some additional, bounded information about the database. We apply this notion to reason about two distinct settings where the notion of differential privacy is of limited use. First, we consider cases, such as in the 2020 US Census [Abowd, 2018], in which some information about the database is released exactly or with small noise. Second, we consider the accumulation of privacy harms for an individual across studies that may not even include the data of this individual. The tools that we develop for bounded-leakage differential privacy allow us reason about privacy loss in these settings, and to show that individuals preserve some meaningful protections.

Subject Classification

ACM Subject Classification
  • Theory of computation → Theory of database privacy and security
  • differential privacy
  • applications
  • privacy
  • leakage
  • auxiliary information


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