Abstract
A probabilistic framework can be used to assess the risk of disclosure of confidential information in statistical databases that use disclosure control mechanisms. The authors show how the method may be used to assess the strengths and weaknesses of two existing disclosure control mechanisms: the query set size restriction control and random sample query control mechanisms. Results indicate that neither scheme provides adequate security. The framework is then further exploited to analyze an alternative scheme combining query set size restriction and random sample query control. It is shown that this combination results in a significant decrease in the risk of disclosure.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">></ETX>
Keywords
Microdata (statistics)Computer scienceSet (abstract data type)Web query classificationConfidentialityData miningQuery optimizationInformation retrievalSample (material)Probabilistic logicSample size determinationQuery languageDatabaseWeb search queryStatisticsMathematicsArtificial intelligenceSearch engineComputer security
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Publication Info
- Year
- 2002
- Type
- article
- Pages
- 278-287
- Citations
- 24
- Access
- Closed
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Cite This
George T. Duncan,
Sumitra Mukherjee
(2002).
Microdata disclosure limitation in statistical databases: query size and random sample query control.
, 278-287.
https://doi.org/10.1109/risp.1991.130795
Identifiers
- DOI
- 10.1109/risp.1991.130795