Publication Details
Biometric-Enabled Authentication Machines: A Survey of Open-Set Real-World Applications
Shmerko Vlad.
Yanushkevich Svetlana
Drahanský Martin, prof. Ing., Ph.D.
Gorodnichy Dmitry
authentication machine, face, iris, fingerprint, access control, biometrics
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.
@article{BUT119819,
author="Shawn {Eastwood} and Vlad. {Shmerko} and Svetlana {Yanushkevich} and Martin {Drahanský} and Dmitry {Gorodnichy}",
title="Biometric-Enabled Authentication Machines: A Survey of Open-Set Real-World Applications",
journal="IEEE Transactions on Human-Machine Systems",
year="2016",
volume="46",
number="2",
pages="231--242",
doi="10.1109/THMS.2015.2412944",
issn="2168-2291",
url="http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=7103330"
}