Technology Gap Navigator: Emerging Design of Biometric-Enabled Risk Assessment Machines

Eastwood, Shawn and Lai, Ken and Yanushkevich, Svetlana and Guest, Richard and Shmerko, Vlad (2018) Technology Gap Navigator: Emerging Design of Biometric-Enabled Risk Assessment Machines. In: BROSIG 2018: Proceedings of the 17th International Conference of the Biometrics Special Interest Group. IEEE. ISBN 978-1-5386-6007-2. E-ISBN 978-3-88579-676-3. (doi:10.23919/BIOSIG.2018.8553056) (KAR id:69282)

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Official URL: http://dx.doi.org/10.23919/BIOSIG.2018.8553056

Abstract

This paper reports the Technology Gap (TG) navigator, a novel tool for individual risk assessment in the layered security infrastructure. It is motivated by the practical need of the biometricenabled security systems design. The tool helps specify the conditions for bridging the identified TGs. The input data for the TG navigator includes 1) a causal description of the TG, 2) statistics regarding the available resources and performances, and 3) the required performance. The output includes generated probabilistic conditions, and the corresponding technology requirements for bridging the targeted TG.

Item Type:	Book section
DOI/Identification number:	10.23919/BIOSIG.2018.8553056
Uncontrolled keywords:	technology gap, causal model, biometrics, risks
Subjects:	T Technology
Divisions:	Divisions > Division of Computing, Engineering and Mathematical Sciences > School of Engineering and Digital Arts
Depositing User:	Richard Guest
Date Deposited:	27 Sep 2018 09:49 UTC
Last Modified:	09 Dec 2022 07:51 UTC
Resource URI:	https://kar.kent.ac.uk/id/eprint/69282 (The current URI for this page, for reference purposes)

University of Kent Author Information

Guest, Richard.

Creator's ORCID:	https://orcid.org/0000-0001-7535-7336
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