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Biometric Recognition: Challenges and Opportunities (2010)
Computer Science and Telecommunications Board (CSTB)

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. "Summary." Biometric Recognition: Challenges and Opportunities. Washington, DC: The National Academies Press, 2010.

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Biometric Recognition: Challenges and Opportunities

Understanding how users interact with systems also merits further attention. The characteristics of the subject population, their attitudes and level of cooperation, the deployment environment, and procedures for measuring performance can all affect the system. Consequently, observation and experimentation in operational systems are required to understand how well biometric applications satisfy their requirements. Because of the challenges inherent in closely observing individuals, with or without their cooperation, human factors are critical to the design of processes for monitoring subjects and operators when assessing the effectiveness of a biometric system.

Another area where research is required is in the systems’ view of biometric recognition, encompassing social, legal, and cultural aspects. Related are social implications of biometric recognition on a large scale. Research is needed, too, on the distinctive information security problems of biometric systems, such as defense against attacks by individuals using fake or previously captured biometric samples and the concealment of biometric traits, and on the protection of biometric reference databases. Decision analysis and threat modeling are other critical areas requiring research advances.

The U.S. government has created or funded several interdisciplinary, academically based research programs that provide a foundation for future work. Research support should aim for greater involvement of scientists and practitioners from relevant disciplines in biometric research, and studies should be published in the open, peer-reviewed scientific literature, with their stringently deidentified biometric samples made widely available to other researchers. A clearinghouse would facilitate efforts toward identifying standards implementation and interoperability issues, characterizing common elements of successful implementations, cataloging lessons learned, and maintaining data as input for testing product robustness and system performance.


Principle: As biometric recognition is deployed in systems of national importance, additional research is needed at virtually all levels of the system (including sensors, data management, human factors, and testing). The research should look at a range of questions from the distinctiveness of biometric traits to optimal ways of evaluating and maintaining large systems over many years.

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