In one dimension, there is essentially just one binomially distributed statistic, bias or correlation, for testing correctness of a key bit in Matsui\u27s Algorithm 1. In multiple dimensions, different statistical approaches for finding the correct key candidate are available. The purpose of this work is to investigate the efficiency of such test in theory and practice, and propose a new key class ranking statistic using distributions based on multidimensional linear approximation and generalisation of the ranking statistic presented by Selc cuk
