  Re-identification algorithms are used in data privacy to measure disclosure
risk. They model the situation in which an adversary attacks a published
database by means of linking the information of this adversary with the
database.
  In this paper we formalize this type of algorithm in terms of true
probabilities and compatible belief functions. The purpose of this work is to
leave aside as re-identification algorithms those algorithms that do not
satisfy a minimum requirement.
