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Differential privacy is a definition of "privacy'" for algorithms that analyze and publish information about statistical databases.
Probabilistic encryption
Shafi Goldwasser and Silvio Micali · 1984
Earlier work this paper cites.
Revealing information while preserving privacy
Irit Dinur and Kobbi Nissim · 2003
Earlier work this paper cites.
Privacy-preserving datamining on vertically partitioned databases
Cynthia Dwork and Kobbi Nissim · 2004
Earlier work this paper cites.
Practical privacy: The SuLQ framework
Avrim Blum, Cynthia Dwork, Frank McSherry, and Kobbi Nissim · 2005
Earlier work this paper cites.
When random sampling preserves privacy
Kamalika Chaudhuri and Nina Mishra · 2006
Earlier work this paper cites.
Differential privacy
Cynthia Dwork · 2006
Cited alongside, same era.
Smooth sensitivity and sampling in private data analysis
Kobbi Nissim, Sofya Raskhodnikova, and Adam Smith · 2007
Cited alongside, same era.
Composition attacks and auxiliary information in data privacy
Srivatsava Ranjit Ganta, Shiva Prasad Kasiviswanathan, and Adam Smith · 2008
Cited alongside, same era.
Privacy: From theory to practice on the map
Ashwin Machanavajjhala, Daniel Kifer, John Abowd, Johannes Gehrke, and Lars Vilhuber · 2008
Cited alongside, same era.
A statistical framework for differential privacy
Larry Wasserman and Shuheng Zhou · 2010
Cited alongside, same era.
On the difficulties of disclosure prevention in statistical databases or the case for differential privacy
Cynthia Dwork and Moni Naor
Cited in the paper.
On the difficulties of disclosure prevention, or the case for differential privacy
Cynthia Dwork and Moni Naor
Cited in the paper.
Our data, ourselves: Privacy via distributed noise generation
Cynthia Dwork, Krishnaram Kenthapadi, Frank McSherry, Ilya Mironov, and Moni Naor
Cited in the paper.
Calibrating noise to sensitivity in private data analysis
Cynthia Dwork, Frank McSherry, Kobbi Nissim, and Adam Smith
Cited in the paper.
No Free Lunch in Data Privacy
Daniel Kifer and Ashwin Machanavajjhala · 2011
Closest in time.
A rigorous and customizable framework for privacy
Daniel Kifer and Ashwin Machanavajjhala · 2012
Closest in time.
Coupled-worlds privacy: Exploiting adversarial uncertainty in private data analysis
Raef Bassily, Adam Groce, Jonathan Katz, and Adam Smith · 2013
Closest in time.
Differential privacy for functions and functional data
Rob Hall, Alessandro Rinaldo, and Larry Wasserman · 2013
Closest in time.
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