Journal article

EASTWOOD Shawn C., SHMERKO Vlad. P., YANUSHKEVICH Svetlana, DRAHANSKÝ Martin and GORODNICHY Dmitry. Biometric-Enabled Authentication Machines: A Survey of Open-Set Real-World Applications. IEEE Transactions on Human-Machine Systems. Washington: Institute of Electrical and Electronics Engineers, 2016, vol. 46, no. 2, pp. 2168-2291. ISSN 2168-2291. Available from:
Publication language:english
Original title:Biometric-Enabled Authentication Machines: A Survey of Open-Set Real-World Applications
Title (cs):Autentizační stroje umožňující biometrii: průzkum aplikací reálného světa s otevřenými množinami
Journal:IEEE Transactions on Human-Machine Systems, Vol. 46, No. 2, Washington, US
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.
   author = {C. Shawn Eastwood and P. Vlad. Shmerko and
	Svetlana Yanushkevich and Martin Drahansk{\'{y}}
	and Dmitry Gorodnichy},
   title = {Biometric-Enabled Authentication Machines: A
	Survey of Open-Set Real-World Applications},
   pages = {2168--2291},
   journal = {IEEE Transactions on Human-Machine Systems},
   volume = 46,
 number = 2,
   year = 2016,
   ISSN = {2168-2291},
   doi = {10.1109/THMS.2015.2412944},
   language = {english},
   url = {}

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