  In a biometric authentication or identification system, the matcher compares
a stored and a fresh template to determine whether there is a match. This
assessment is based on both a similarity score and a predefined threshold. For
better compliance with privacy legislation, the matcher can be built upon a
privacy-preserving distance. Beyond the binary output (`yes' or `no'), most
schemes may perform more precise computations, e.g., the value of the distance.
Such precise information is prone to leakage even when not returned by the
system. This can occur due to a malware infection or the use of a weakly
privacy-preserving distance, exemplified by side channel attacks or partially
obfuscated designs. This paper provides an analysis of information leakage
during distance evaluation. We provide a catalog of information leakage
scenarios with their impacts on data privacy. Each scenario gives rise to
unique attacks with impacts quantified in terms of computational costs, thereby
providing a better understanding of the security level.
