Biometrics seems to be going gang busters in the developing world. I fear we’re seeing a new wave of technological imperialism. In this post I will examine whether the biometrics field is mature enough for the lofty social goal of empowering the world’s poor and disadvantaged with “identity”.
The independent Center for Global Development has released a report “Identification for Development: The Biometrics Revolution” which looks at 160 different identity programs using biometric technologies. By and large, it’s a study of the vital social benefits to poor and disadvantaged peoples when they gain an official identity and are able to participate more fully in their countries and their markets.
The CGD report covers some of the kinks in how biometrics work in the real world, like the fact that a minority of people can be unable to enroll and they need to be subsequently treated carefully and fairly. But I feel the report takes biometric technology for granted. In contrast, independent experts have shown there is insufficient science for biometric performance to be predicted in the field. I conclude biometrics are not ready to support such major public policy initiatives as ID systems.
The state of the science of biometrics
I recently came across a weighty assessment of the science of biometrics presented by one of the gurus, Jim Wayman, and his colleagues to the NIST IBPC 2010 biometric testing conference. The paper entitled “Fundamental issues in biometric performance testing: A modern statistical and philosophical framework for uncertainty assessment” should be required reading for all biometrics planners and pundits.
Here are some important extracts:
[Technology] testing on artificial or simulated databases tells us only about the performance of a software package on that data. There is nothing in a technology test that can validate the simulated data as a proxy for the “real world”, beyond a comparison to the real world data actually available. In other words, technology testing on simulated data cannot logically serve as a proxy for software performance over large, unseen, operational datasets. [p15, emphasis added].
In a scenario test, [False Non Match Rate and False Match Rate] are given as rates averaged over total transactions. The transactions often involve multiple data samples taken of multiple persons at multiple times. So influence quantities extend to sampling conditions, persons sampled and time of sampling. These quantities are not repeatable across tests in the same lab or across labs, so measurands will be neither repeatable nor reproducible. We lack metrics for assessing the expected variability of these quantities between tests and models for converting that variability to uncertainty in measurands.[p17].
To explain, a biometric “technology test” is when a software package is exercised on a standardised data set, usually in a bake-off such as NIST’s own biometric performance tests over the years. And a “scenario test” is when the biometric system is tested in the lab using actual test subjects. The meaning of the two dense sentences underlined by me in the extracts is: technology test results from one data set do not predict performance on any other data set or scenario, and biometrics practitioners still have no way to predict the accuracy of their solutions in the real world.
The authors go on:
[To] report false match and false non-match performance metrics for [iris and face recognition] without reporting on the percentage of data subjects wearing contact lenses, the period of time between collection of the compared image sets, the commercial systems used in the collection process, pupil dilation, and lighting direction is to report “nothing at all”. [pp17-18].
And they conclude, amongst other things:
[False positive and false negative] measurements have historically proved to be neither reproducible nor repeatable except in very limited cases of repeated execution of the same software package against a static database on the same equipment. Accordingly, “technology” test metrics have not aligned well with “scenario” test metrics, which have in turn failed to adequately predict field performance. [p22].
The limitations of biometric testing has repeatedly been stressed by no less an authority than the US FBI. In their State-of-the-Art Biometric Excellence Roadmap (SABER) Report the FBI cautions that:
For all biometric technologies, error rates are highly dependent upon the population and application environment. The technologies do not have known error rates outside of a controlled test environment. Therefore, any reference to error rates applies only to the test in question and should not be used to predict performance in a different application. [p4.10]
The SABER report also highlighted a widespread weakness in biometric testing, namely that accuracy measurements usually only look at accidental errors:
The intentional spoofing or manipulation of biometrics invalidates the “zero effort imposter” assumption commonly used in performance evaluations. When a dedicated effort is applied toward fooling biometrics systems, the resulting performance can be dramatically different. [p1.4]
A few years ago, the Future of Identity in the Information Society Consortium (“FIDIS”, a research network funded by the European Community’s Sixth Framework Program) wrote a major report on forensics and identity systems. FIDIS looked at the spoofability of many biometrics modalities in great detail (pp 28-69). These experts concluded:
Concluding, it is evident that the current state of the art of biometric devices leaves much to be desired. A major deficit in the security that the devices offer is the absence of effective liveness detection. At this time, the devices tested require human supervision to be sure that no fake biometric is used to pass the system. This, however, negates some of the benefits these technologies potentially offer, such as high-throughput automated access control and remote authentication. [p69]
Biometrics in public policy
To me, biometrics is in an appalling and astounding state of affairs. The prevailing public understanding of how these technologies work is utopian, based probably on nothing more than science fiction movies, and the myth of biometric uniqueness. In stark contrast, scientists warn there is no telling how biometrics will work in the field, and the FBI warns that bench testing doesn’t predict resistance to attack. It’s very much like the manufacturer of a safe confessing to a bank manager they don’t know how it will stand up in an actual burglary.
This situation has bedeviled enterprise and financial services security for years. Without anyone admitting it, it’s possible that the slow uptake of biometrics in retail and banking (save for Japan and their odd hand vein ATMs) is a result of hard headed security officers backing off when they look deep into the tech. But biometrics is going gang busters in the developing world, with vendors thrilling to this much bigger and faster moving market.
The stakes are so very high in national ID systems, especially in the developing world, where resistance to their introduction is relatively low, for various reasons. I’m afraid there is great potential for technological imperialism, given the historical opacity of this industry and its reluctance to engage with the issues.
To be sure vendors are not taking unfair advantage of the developing world ID market, they need to answer some questions:
- Firstly, how do they respond to Jim Wayman, the FIDIS Consortium and the FBI? Is it possible to predict how finger print readers, face recognition and iris scanners are going to operate, over years and years, in remote and rural areas?
- In particular, how good is liveness detection? Can these solutions be trusted in unattended operation for such critical missions as e-voting?
- What contingency plans are in place for biometric ID theft? Can the biometric be cancelled and reissued if compromised? Wouldn’t it be catastrophic for the newly empowered identity holder to find themselves cut out of the system if their biometric can no longer be trusted?