Modeling Projections in Microaggregation
Jordi Nin, Vicenç Torra · 2014
Microaggregation is a method used by statistical agencies to limit the disclosure of sensitive microdata. It has been proven that microaggrega-tion is an NP-hard problem when more than one variable is microag-gregated at the same time. To solve this problem in a heuristic way, a few methods based on projections have been introduced in the litera-ture. The main drawback of such methods is that the projected axis is computed maximizing a statisti-cal property (e.g., the global vari-ance of the data), disregarding the fact that the aim of microaggrega-tion is to keep the disclosure risk as low as possible for all records. In this paper we present some pre-liminary results on the application of aggregation functions for comput-ing the projected axis. We show that, using the Sugeno integral to calculate the projected axis, we can reduce in some cases the disclosure risk of the protected data (when pro-jected microaggregation is used).