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.