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Recently, the permutation paradigm has been proposed in data anonymization todescribe any micro data masking method as permutation, paving the way forperforming meaningful analytical comparisons of methods, something that isdifficult currently in statistical disclosure control research. This paperexplores some consequences of this paradigm by establishing some class ofuniversal measures of disclosure risk and information loss that can be used forthe evaluation and comparison of any method, under any parametrization andindependently of the characteristics of the data to be anonymized. Thesemeasures lead to the introduction in data anonymization of the concepts ofdominance in disclosure risk and information loss, which formalise the factthat different parties involved in micro data transaction can all havedifferent sensitivities to privacy and information.

On some consequences of the permutation paradigm for data anonymization:  centrality of permutation matrices, universal measures of disclosure risk and  information loss, evaluation by dominance