Fuzzy Microaggregation for Microdata Protection
Josep Domingo-Ferrer*, and Vicenç Torra**
*Department of Computing Engineering and Maths - ETSE, Universitat Rovira i Virgili, Av. Països Catalans 26, 43007 Tarragona, Catalonia, Spain
**Institut d’Investigació en Intel-ligèencia Artificial - CSIC, Campus UAB s/n, 08193 Bellaterra, Catalonia, Spain
Received:January 31, 2003Accepted:February 20, 2003Published:June 20, 2003
Keywords:clustering, fuzzy c-means, microaggregation, aggregation, masking methods, data protection, national statistical offices
In this work we describe a microdata protection method based on the use of fuzzy clustering and, more specifically, using fuzzy c-means. Microaggregation is a well-known masking method for microdata protection used by National Statistical Offices. Given a set of objects described in terms of a set of variables, this method consists on building a partition of the objects and then replace the original evaluation for each variable by the aggregates of each partition. This is, the values in a given cluster are aggregated –fused– and used instead of the original ones. As the problem of finding the best partition for microdata protection is an NP problem, heuristic methods are considered in the literature. Our approach uses fuzzy c-means for building a fuzzy partition, instead of a crisp one.
Cite this article as:J. Domingo-Ferrer and V. Torra, “Fuzzy Microaggregation for Microdata Protection,” J. Adv. Comput. Intell. Intell. Inform., Vol.7 No.2, pp. 153-159, 2003.Data files: