Biometric-Enabled Authentication Machines: A Survey of Open-Set Real-World Applications
| Autor: | V. P. Shmerko, Dmitry O. Gorodnichy, Svetlana Yanushkevich, Shawn C. Eastwood, Martin Drahansky |
|---|---|
| Rok vydání: | 2016 |
| Předmět: |
Biometrics
Computer Networks and Communications Computer science Bayesian probability Iris recognition Open set Human Factors and Ergonomics Access control 02 engineering and technology Machine learning computer.software_genre Artificial Intelligence Taxonomy (general) 0502 economics and business 0202 electrical engineering electronic engineering information engineering Risk management 050210 logistics & transportation Authentication business.industry 05 social sciences Computer Science Applications Human-Computer Interaction Control and Systems Engineering Signal Processing 020201 artificial intelligence & image processing Artificial intelligence business computer |
| Zdroj: | IEEE Transactions on Human-Machine Systems. 46:231-242 |
| ISSN: | 2168-2305 2168-2291 |
| DOI: | 10.1109/thms.2015.2412944 |
| Popis: | This paper revisits the concept of an authentication machine (A-machine) that aims at identifying/verifying humans. Although A-machines in the closed-set application scenario are well understood and commonly used for access control utilizing human biometrics (face, iris, and fingerprints), open-set applications of A-machines have yet to be equally characterized. This paper presents an analysis and taxonomy of A-machines, trends, and challenges of open-set real-world applications. This paper makes the following contributions to the area of open-set A-machines: 1) a survey of applications; 2) new novel life cycle metrics for theoretical, predicted, and operational performance evaluation; 3) a new concept of evidence accumulation for risk assessment; 4) new criteria for the comparison of A-machines based on the notion of a supporting assistant; and 5) a new approach to border personnel training based on the A-machine training mode. It offers a technique for modeling A-machines using belief (Bayesian) networks and provides an example of this technique for biometric-based e-profiling. |
| Databáze: | OpenAIRE |
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