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SIGMOD
2011
ACM
179views Database» more  SIGMOD 2011»
13 years 20 days ago
No free lunch in data privacy
Differential privacy is a powerful tool for providing privacypreserving noisy query answers over statistical databases. It guarantees that the distribution of noisy query answers...
Daniel Kifer, Ashwin Machanavajjhala
ICDE
2005
IEEE
147views Database» more  ICDE 2005»
14 years 3 months ago
Privacy-Preserving Top-K Queries
Processing of top-k queries has been attracting considerable attention. Much of the work assumes distributed data, with each site holding a different set of attributes for the sam...
Jaideep Vaidya, Chris Clifton
FC
2009
Springer
67views Cryptology» more  FC 2009»
14 years 1 months ago
Privacy-Preserving Classifier Learning
We present an efficient protocol for the privacy-preserving, distributed learning of decision-tree classifiers. Our protocol allows a user to construct a classifier on a database h...
Justin Brickell, Vitaly Shmatikov
PODS
2011
ACM
163views Database» more  PODS 2011»
13 years 21 days ago
Provenance views for module privacy
Scientific workflow systems increasingly store provenance information about the module executions used to produce a data item, as well as the parameter settings and intermediate...
Susan B. Davidson, Sanjeev Khanna, Tova Milo, Debm...
EUROCRYPT
2006
Springer
14 years 1 months ago
Our Data, Ourselves: Privacy Via Distributed Noise Generation
In this work we provide efficient distributed protocols for generating shares of random noise, secure against malicious participants. The purpose of the noise generation is to crea...
Cynthia Dwork, Krishnaram Kenthapadi, Frank McSher...