There has been a lot of research on on the "zoo" of biometrics. Doddington's zoo or the biometric menagerie make reasonable search terms. The idea is that you

There has been a lot of research on on the "zoo" of biometrics. Doddington's zoo or the biometric menagerie make reasonable search terms. The idea is that you have a few classes of errors in any calibrated heuristic system, and biometrics fall prey to the same ones. The individuals that trigger these errors were given animal names. Given a large enough population, most of the population will be "sheep" - the system works as intended for these. Some individuals will be prone to false positives. They will pass the system even though they should fail. We'll call these wolves. Others will be prone to false negatives - they will fail even when they should pass. Goats. Lambs are a group that is easy to mimic - so others will be mistaken for them once they are in the system, so they sort of perpetuate wolves by having a really generic set of distinguishing traits. I think this zoo was extended for other unique cases and other animals, but I'm having trouble finding links to the most popular research papers in this series. The research prompting the posted article seems to be about identifying "wolves" - a good demonstration of the validity of Doddington's theories. * Wolves are technically just good mimickers, I'm simplifying a bit above.