Interpreting Epsilon of Differential Privacy in Terms of Advantage in Guessing or Approximating Sensitive Attributes

Differential privacy

Cynthia Dwork · 2006

Earlier work this paper cites.

Privacy integrated queries: an extensible platform for privacy-preserving data analysis

Frank McSherry · 2009

Earlier work this paper cites.

How much is enough? choosing ϵ \epsilon for differential privacy

Jaewoo Lee and Chris Clifton · 2011

Earlier work this paper cites.

Differential identifiability

Jaewoo Lee and Chris Clifton · 2012

Earlier work this paper cites.

Broadening the scope of differential privacy using metrics

Konstantinos Chatzikokolakis, Miguel E. Andrés, Nicolás Emilio Bordenabe, and Catuscia Palamidessi · 2013

Earlier work this paper cites.

The composition theorem for differential privacy

Original

Sewoong Oh and Pramod Viswanath · 2013

Cited alongside, same era.

Generalized differential privacy: Regions of priors that admit robust optimal mechanisms

Ehab ElSalamouny, Konstantinos Chatzikokolakis, and Catuscia Palamidessi · 2014

Cited alongside, same era.

Blowfish privacy: tuning privacy-utility trade-offs using policies

Xi He, Ashwin Machanavajjhala, and Bolin Ding · 2014

Cited alongside, same era.

Pufferfish: A framework for mathematical privacy definitions

Daniel Kifer and Ashwin Machanavajjhala · 2014

Cited alongside, same era.

Pufferfish: A framework for mathematical privacy definitions

Daniel Kifer and Ashwin Machanavajjhala · 2014

Cited alongside, same era.

Geo-indistinguishability: A principled approach to location privacy

Konstantinos Chatzikokolakis, Catuscia Palamidessi, and Marco Stronati · 2015

Later among the works it cites.

Differential privacy: Now it’s getting personal

Hamid Ebadi, David Sands, and Gerardo Schneider · 2015

Later among the works it cites.

An algorithm for the matrix lambert w function

M. Fasi, N. Higham, and B. Iannazzo · 2015

Later among the works it cites.

Privacy loss classes: The central limit theorem in differential privacy

David M. Sommer, Sebastian Meiser, and Esfandiar Mohammadi · 2019

Closest in time.

Differential Privacy with Flexible Metrics, 2020

Peeter Laud, Alisa Pankova, and Martin Pettai · 2020

Closest in time.