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Disclosure Control of Business Microdata: A Density‐Based Approach

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  • Daniela Ichim

Abstract

For continuous key variables, a measure of the individual risk of disclosure is proposed. This risk measure, the local outlier factor, estimates the density around a unit. A selective masking method based on the nearest‐neighbour principle and microaggregation is also introduced. Some results of an application to the Italian sample of the Community Innovation Survey are presented. Pour les clefs d'identification continues, une mesure du risque individuel de réidentification est proposée. Cette mesure, le facteur de donnée aberrante locale, estime la densité autour d'une unité. Une méthode de protection sélective, basée sur le principe des plus proches unités et sur la micro‐agrégation, est également introduite. Des résultats de l'application à l'anonymisation de fichier de données individuelles provenant de l'échantillon italien de l'enquête « Community Innovation » sont presentés.

Suggested Citation

  • Daniela Ichim, 2009. "Disclosure Control of Business Microdata: A Density‐Based Approach," International Statistical Review, International Statistical Institute, vol. 77(2), pages 196-211, August.
    • Handle: RePEc:bla:istatr:v:77:y:2009:i:2:p:196-211
    DOI: 10.1111/j.1751-5823.2009.00079.x
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    References listed on IDEAS

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    1. Zeileis, Achim & Kleiber, Christian & Kramer, Walter & Hornik, Kurt, 2003. "Testing and dating of structural changes in practice," Computational Statistics & Data Analysis, Elsevier, vol. 44(1-2), pages 109-123, October.
    2. Paass, Gerhard, 1988. "Disclosure Risk and Disclosure Avoidance for Microdata," Journal of Business & Economic Statistics, American Statistical Association, vol. 6(4), pages 487-500, October.
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