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» Continuous privacy preserving publishing of data streams
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VLDB
2007
ACM
108views Database» more  VLDB 2007»
14 years 7 months ago
Time Series Compressibility and Privacy
In this paper we study the trade-offs between time series compressibility and partial information hiding and their fundamental implications on how we should introduce uncertainty ...
Spiros Papadimitriou, Feifei Li, George Kollios, P...
ISI
2008
Springer
13 years 7 months ago
A framework for privacy-preserving cluster analysis
Abstract--Releasing person-specific data could potentially reveal sensitive information of individuals. k-anonymization is a promising privacy protection mechanism in data publishi...
Benjamin C. M. Fung, Ke Wang, Lingyu Wang, Mourad ...
VLDB
2006
ACM
122views Database» more  VLDB 2006»
14 years 7 months ago
A secure distributed framework for achieving k-anonymity
k-anonymity provides a measure of privacy protection by preventing re-identification of data to fewer than a group of k data items. While algorithms exist for producing k-anonymous...
Wei Jiang, Chris Clifton
ICDE
2012
IEEE
221views Database» more  ICDE 2012»
11 years 10 months ago
DPCube: Releasing Differentially Private Data Cubes for Health Information
—We demonstrate DPCube, a component in our Health Information DE-identification (HIDE) framework, for releasing differentially private data cubes (or multi-dimensional histogram...
Yonghui Xiao, James J. Gardner, Li Xiong
ICDM
2010
IEEE
150views Data Mining» more  ICDM 2010»
13 years 5 months ago
Probabilistic Inference Protection on Anonymized Data
Background knowledge is an important factor in privacy preserving data publishing. Probabilistic distributionbased background knowledge is a powerful kind of background knowledge w...
Raymond Chi-Wing Wong, Ada Wai-Chee Fu, Ke Wang, Y...