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ICDE
2012
IEEE

DPCube: Releasing Differentially Private Data Cubes for Health Information

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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 histograms) for sensitive data. HIDE is a framework we developed for integrating heterogenous structured and unstructured health information and provides methods for privacy preserving data publishing. The DPCube component uses differentially private access mechanisms and an innovative 2-phase multidimensional partitioning strategy to publish a multi-dimensional data cube or histogram that achieves good utility while satisfying differential privacy. We demonstrate that the released data cubes can serve as a sanitized synopsis of the raw database and, together with an optional synthesized dataset based on the data cubes, can support various Online Analytical Processing (OLAP) queries and learning tasks.
Yonghui Xiao, James J. Gardner, Li Xiong
Added 27 Sep 2012
Updated 27 Sep 2012
Type Journal
Year 2012
Where ICDE
Authors Yonghui Xiao, James J. Gardner, Li Xiong
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