Association rules mining is a problem that gave rise to a rich literature, especially in classic binary bidimensional data. In particular, the relation between closed sets and association rules is well understood. This is not the case in multidimensional data. In this paper, we show that the knowledge of the closed n-sets of a multidimensional boolean tensor is enough to allow for the derivation of the confidence of every multidimensional association rule.