TY - GEN
T1 - Versatile publishing for privacy preservation
AU - Jin, Xin
AU - Zhang, Mingyang
AU - Zhang, Nan
AU - Das, Gautam
PY - 2010
Y1 - 2010
N2 - 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.
AB - 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.
UR - http://www.scopus.com/inward/record.url?scp=77956224515&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=77956224515&partnerID=8YFLogxK
U2 - 10.1145/1835804.1835851
DO - 10.1145/1835804.1835851
M3 - Conference contribution
AN - SCOPUS:77956224515
SN - 9781450300551
T3 - Proceedings of the ACM SIGKDD International Conference on Knowledge Discovery and Data Mining
SP - 353
EP - 362
BT - KDD'10 - Proceedings of the 16th ACM SIGKDD International Conference on Knowledge Discovery and Data
T2 - 16th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, KDD-2010
Y2 - 25 July 2010 through 28 July 2010
ER -