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PODS
2010
ACM
306views Database» more  PODS 2010»
15 years 4 months ago
Optimizing linear counting queries under differential privacy
Differential privacy is a robust privacy standard that has been successfully applied to a range of data analysis tasks. But despite much recent work, optimal strategies for answe...
Chao Li, Michael Hay, Vibhor Rastogi, Gerome Mikla...
FOCS
2010
IEEE
14 years 9 months ago
Boosting and Differential Privacy
Boosting is a general method for improving the accuracy of learning algorithms. We use boosting to construct improved privacy-preserving synopses of an input database. These are da...
Cynthia Dwork, Guy N. Rothblum, Salil P. Vadhan
KDD
2008
ACM
163views Data Mining» more  KDD 2008»
16 years 6 days ago
The cost of privacy: destruction of data-mining utility in anonymized data publishing
Re-identification is a major privacy threat to public datasets containing individual records. Many privacy protection algorithms rely on generalization and suppression of "qu...
Justin Brickell, Vitaly Shmatikov
DEXAW
2003
IEEE
131views Database» more  DEXAW 2003»
15 years 5 months ago
Privacy and Trusted Computing
This paper examines a model of trusted computing wherein a computing platform is able to make assertions about its current software configuration that may be trusted by the user ...
Juan Manuel González Nieto, Ed Dawson, Eiji...
ICDE
2009
IEEE
141views Database» more  ICDE 2009»
16 years 1 months ago
Privacy Preserving Publishing on Multiple Quasi-identifiers
In some applications of privacy preserving data publishing, a practical demand is to publish a data set on multiple quasi-identifiers for multiple users simultaneously, which poses...
Jian Pei, Yufei Tao, Jiexing Li, Xiaokui Xiao