On the disclosure risk of multivariate microaggregation

Authors:
Jordi Nin;Javier Herranz;Vicenç Torra
Affiliations:
IIIA, Artificial Intelligence Research Institute, CSIC, Spanish National Research Council, Campus UAB s/n, 08193 Bellaterra, Catalonia, Spain;IIIA, Artificial Intelligence Research Institute, CSIC, Spanish National Research Council, Campus UAB s/n, 08193 Bellaterra, Catalonia, Spain;IIIA, Artificial Intelligence Research Institute, CSIC, Spanish National Research Council, Campus UAB s/n, 08193 Bellaterra, Catalonia, Spain
Venue:
Data & Knowledge Engineering
Year:
2008

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Abstract

The aim of data protection methods is to protect a microdata file both minimizing the disclosure risk and preserving the data utility. Microaggregation is one of the most popular such methods among statistical agencies. Record linkage is the standard mechanism used to measure the disclosure risk of a microdata protection method. However, only standard, and quite generic, record linkage methods are usually considered, whereas more specific record linkage techniques can be more appropriate to evaluate the disclosure risk of some protection methods. In this paper we present a new record linkage technique, specific for microaggregation, which obtains more correct links than standard techniques. We have tested the new technique with MDAV microaggregation and two other microaggregation methods, based on projections, that we propose here for the first time. The direct consequence is that these microaggregation methods have a higher disclosure risk than believed up to now.