Microaggregation is a family of masking methods for statistical disclosure control of numerical microdata (although variants for categorical data exist). The rationale behind microaggregation is that confidentiality rules in use allow publication of microdata sets if records correspond to groups of k or more individuals, where no individual dominates (i.e., contributes too much to) the group and k is a threshold value. Strict application of such confidentiality rules leads to replacing individual values with values computed on small aggregates (microaggregates) prior to publication. This is the basic principle of microaggregation.
To obtain microaggregates in a microdata set with n records, these are combined to form g groups of size at least k. For each attribute, the average value over each group is computed and is used to replace each of the original averaged values. Groups are formed using a criterion of maximal similarity. Once the procedure has been completed, the...
- 4.Hundepool A, Van de Wetering A, Ramaswamy R, Franconi L, Capobianchi A, DeWolf P-P, Domingo-Ferrer J, Torra V, Brand R, Giessing S. μ-ARGUS version 4.0 software and user’s manual. Statistics Netherlands, Voorburg, May 2005. http://neon.vb.cbs.nl/casc