Authentication over noisy data with the use of memory containing metric functions

We propose an authentication scheme where the verifier makes the decision based on the value of the metric function, which is assigned depending on the type of the vector stored in the database at the enrollment stage. The scheme has a better performance than the maximum likelihood verification algorithm even for binary symmetric channels.