A modest little quote from a biometrics expert caught my eye this week. Neil Fisher, VP of Global Security Solutions at Unisys was cited describing the False Acceptance Rate of iris scanning as “in the region of 0.1%”. See Believing in biometrics, at “Airport Technology”, http://www.airport-technology.com/features/featurebelieving-in-biometrics.
This figure is, to put it mildly, rather less than what we’ve been led to believe by iris scanning proponents over the years.
It is widely reported that the probability of two randomly selected irises matching is one in 10 to the power of 78 [1]. This is indeed a staggering denominator, far greater than the number of stars in all the galaxies in all the universe [Yet that number is near meaningless if the iris scanning equipments isn’t perfect. Consider that there are 100 billion stars in the Milky Way but that figure doesn’t predict the odds of two people picking out the same star with the naked eye, which is one in a few hundred or worse depending on the lighting conditions.]
Yet the recognised inventor of iris recognition, John Daugman of Cambridge University, never claimed his method was as good as all that. In 2000, Daugman published a technical paper [2] on iris detection decision thresholds. Based on data from an ophthalmology research database, his calculations implied [3] a False Match rate as low as one in 10 to the power of 14.
In 2005 Daugman experimentally verified his very low error rate claim using data on over 600,000 individuals sampled in the United Arab Emirates’ immigration security system [4]. He reported that “False Match rate is less than 1 in 200 billion” or one in 10 to the power of 11. But it should have been clear to all that the result would be very best case, for border security biometrics systems impose tight control over image quality and lighting conditions for both enrolment and subsequent capture events; without such control, measurement fidelity suffers.
And indeed, independent government testing of iris biometrics, while impressive, show error rates millions of times worse than Daugman’s estimates. For example, the UK Government in 2001 found a False Match rate of 0.0001% or one in a million [5].
And now we have a leading biometrics implementer say that in practice, the iris False Match Rate is typically 0.1% or a pretty ordinary one in 1,000. If that’s the real life benchmark, then the folkloric figure of one in 10 to the power of 78 represents an exaggeration of one thousand, trillion, trillion, trillion, trillion, trillion, trillion times.
Literally.