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Versatile Publishing For Privacy Preservation

Versatile Publishing For Privacy Preservation

This video was recorded at 16th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD), Washington 2010. Motivated by the insufficiency of the existing quasi-identifier/sensitive-attribute (QI-SA) framework on modeling real-world privacy requirements for data publishing, we propose a novel versatile publishing scheme with which privacy requirements can be specified as an arbitrary set of privacy rules over attributes in the microdata table. To enable versatile publishing, we introduce the Guardian Normal Form (GNF), a novel method of publishing multiple sub-tables such that each sub-table is anonymized by an existing QI-SA publishing algorithm, while the combination of all published tables guarantees all privacy rules. We devise two algorithms, Guardian Decomposition (GD) and Utility-aware Decomposition (UAD), for decomposing a microdata table into GNF, and present extensive experiments over real-world datasets to demonstrate the effectiveness of both algorithms.


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