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VLDB
2006
ACM

A secure distributed framework for achieving k-anonymity

14 years 2 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 data, the model has been that of a single source wanting to publish data. Due to privacy issues, it is common that data from different sites cannot be shared directly. Therefore, this paper presents a two-party framework along with an application that generates k-anonymous data from two vertically partitioned sources without disclosing data from one site to the other. The framework is privacy preserving in the sense that it satisfies the secure definition commonly defined in the literature of Secure Multiparty Computation. Keywords k-Anonymity ? Privacy ? Security
Wei Jiang, Chris Clifton
Added 05 Dec 2009
Updated 05 Dec 2009
Type Conference
Year 2006
Where VLDB
Authors Wei Jiang, Chris Clifton
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