  Recently, the permutation paradigm has been proposed in data anonymization to
describe any micro data masking method as permutation, paving the way for
performing meaningful analytical comparisons of methods, something that is
difficult currently in statistical disclosure control research. This paper
explores some consequences of this paradigm by establishing some class of
universal measures of disclosure risk and information loss that can be used for
the evaluation and comparison of any method, under any parametrization and
independently of the characteristics of the data to be anonymized. These
measures lead to the introduction in data anonymization of the concepts of
dominance in disclosure risk and information loss, which formalise the fact
that different parties involved in micro data transaction can all have
different sensitivities to privacy and information.
