Biometric Recognition Challenges and Opportunities (2010) / Chapter Skim
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5 Research Opportunities and the Future of Biometrics
5 Research Opportunities and the Future of Biometrics
Pages 116-138
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From page 116... ...
In fact, many biometric systems have been suc cessfully deployed. For example, hand geometry systems serve to control access to, among others, university dorms, nuclear power plants, and factories, where they record time and location.1 Automated fingerprint identification systems (AFISs)
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From page 117... ...
If there is a pressing public need for these applications, and if it is determined that biometric systems and technologies are the most appropriate way to implement them, then our understanding of the underlying science and technology must be robust enough to support the applica tions.2 There is no substitute for realistic performance evaluations and sustained investment in research and development (R&D) to improve human recognition solutions and biometric systems.3 The rest of this chapter outlines a research agenda focusing on (1)
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From page 118... ...
But as these other agendas demonstrate, there are numerous opportunities for deeper understanding of these systems at almost every level. This section lays out several technical and engineering areas the committee believes would benefit from sustained research and further investigation: human factors, understanding the underlying phenomena, modality-related technical challenges, opportunities to advance testing and evaluation, statistical engineering aspects, and issues of scale.
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From page 119... ...
This assumption has not, however, been confirmed by scientific methods for specific biometric characteristics, either by prospectively collecting and analyzing biometric samples and feature patterns or by exploiting databases of samples or feature patterns assembled for other purposes. A broad and representative sampling of the population in which distinctiveness is being evaluated should be obtained and a minimum quality specification should be set to which biometric samples should conform.
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From page 120... ...
This becomes a particularly important question at scale -- that is, when the systems are expected to cope with large user populations and/or large reference databases. Even in DNA analysis, there has been controversy and uncertainty over how to estimate distinctiveness.9 In biometric systems, "ground truth" -- the collection of facts about biometric data subjects and recogni tion events to allow evaluation of system performance -- is challenging, particularly for passive surveillance systems, where failures to acquire may be difficult to detect.10 There are also open questions about the stability of the underlying traits -- how persistent (stable)
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From page 121... ...
Improving robustness to attacks, including the presentation of falsified biometric traits (perhaps, for exam ple, through automated artifact detection)
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From page 122... ...
11 Information security research is needed that addresses the unique prob lems of biometric systems, such as preventing attacks based on the presentation of fake biometrics, the replay of previously captured biometric samples, and the concealment of biometric traits. Developing techniques 11 See NRC, Toward a Safer and More Secure Cyberspace, Washington, D.C.: The National Academies Press (2007)
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From page 123... ...
The work over the last decade within the international standards community to reach agreement on fundamental concepts, such as how error rates are to be measured, has clarified the application of test methods under the usual laboratory conditions for biometric systems deployments.13 Guidance for potential deployers of biometric systems on what is even a useful and appropriate initial set of questions to ask before getting into the details of modalities and so forth, as developed by a number of groups, has 12 NIST's emerging National Voluntary Laboratory Accreditation Program (NVLAP) for biometrics represents progress in formalizing testing programs but does not yet provide specific testing methods required for different products and applications and does not yet address operational testing.
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From page 124... ...
Although the international standards community has made progress in developing a coherent set of best practices for technol ogy and scenario testing, guidelines for operational testing are still under development and have been slowed by the community's general lack of experience with these evaluations and a lack of published methods and results.15 Designing a system and corresponding tests that can cope with ongoing data collection is a significant challenge, making it difficult for a potential user of biometric systems, such as a federal agency, to determine how well a vendor's technology might operate in its applications and to assess progress in biometric system performance. Careful process and quality control analysis -- as distinct from traditional, standardized testing of biometric systems that focuses on match performance for a test data set -- at all stages of the system life cycle is essential.
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From page 125... ...
Whether the Privacy Act provides the latitude to use operational biometric and biometric-related data for large-scale research and testing purposes (during acquisition and operation) so long as data privacy and integrity are adequately protected is subject to interpretation.
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From page 126... ...
When setting baseline error rates, it is important
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From page 127... ...
More research is needed to understand this. Such questions are related to the distinctiveness and stability of the underlying biometric traits, discussed above.
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From page 128... ...
Guidance for potential users of biometric systems on an appropriate initial set of questions to ask before getting into the details of modalities and so forth has proven particularly useful.19 Testing When Data Changes Designing a system and tests that can cope with ongoing data collec tion after it has been deployed is a significant challenge. The characteris tics of the data may change from what was assumed during testing.
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From page 129... ...
This section outlines some potential research questions in statistical engineering and biometric systems that merit attention. Statistical approaches come into play with respect to the user popula tions, including cross-sectional and longitudinal studies of the variability of various biometric modalities over time, the association of biometrics with demographic and medical factors, and the effects of demographic factors and physical characteristics on failure to acquire and error rates.
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From page 130... ...
For instance, one question is this: How does the number of persons who have references in the enrolled database affect the speed of the sys tem and its error rates? For some applications and associated algorithmic approaches, the size of the database might not matter if typical operation involves only a one-to-one comparison -- that is, one set of submitted samples being compared to one set of enrollment records.
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From page 131... ...
Using hardware linearly proportional to the database size is expensive. Coarse pattern classification offers substantial scaling advantages even when single mea sures are available and even more advantage with multiple measures -- for example, fingerprints from multiple fingers -- but can add to the nonmatch error rates.
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From page 132... ...
Unfortunately, there are few rigorous studies of these contexts. Below is a framework for developing a portfolio of future research investigations that could help biometric systems better cope and perform within their cultural and social contexts.
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From page 133... ...
One part of the design process for particular systems or, more realistically, for a particular class of systems might be to develop data that predict how well the biometric system will perform in a target community and on factors that may make the system more acceptable to that community. Predictive aspects may just have a statis tical relationship with subject compliance or community acceptability, while acceptability factors probably have a causal relationship.
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From page 134... ...
The more common approach is to survey data subjects who have just encountered an operational system to elicit their opinions,23 but even this approach has rarely been applied. Aspects that predict the extent and nature of community acceptability can be discovered and confirmed using either or both of two basic research strategies: field studies of similar deployments using ethno graphic tools -- as indicated for participant compliance above, or focus groups that are asked to discuss how they view various characteristics of a biometric system such as are common in marketing studies.
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From page 135... ...
(The program has a ready customer: the FBI's Criminal Justice Information Center in Clarksburg, West Virginia.) • The sourcing of the technology is crucial to the government's successful deployment of technological and information systems, including biometric systems.
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From page 136... ...
• To what extent are privacy requirements, interagency control issues, and policy constraints, or the perception thereof, inhibiting the research use and sharing of existing biometric data? • What belief sets, if any, lead to an aversion to certain biometric technologies?
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From page 137... ...
, be appropriately randomized, and represent the populations of interest to target applications. To the extent consistent with privacy and security, the results of the studies should be published in the peer-reviewed scientific literature and the biometric samples used made widely available to other researchers.
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From page 138... ...
The system will specifically address the pos sibility that malicious individuals may be involved in the design and/or operation of the system itself. • It will recognize that biometric traits are inherently not secret and will implement processes to minimize both privacy risks and risks of misrecognition arising from this fact.
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