Using a Bayesian averaging model for estimating the reliability of decisions in multimodal biometrics

2.50
Hdl Handle:
http://hdl.handle.net/10547/270799
Title:
Using a Bayesian averaging model for estimating the reliability of decisions in multimodal biometrics
Authors:
Maple, Carsten; Schetinin, Vitaly ( 0000-0003-1826-0153 )
Abstract:
The issue of reliable authentication is of increasing importance in modern society. Corporations, businesses and individuals often wish to restrict access to logical or physical resources to those with relevant privileges. A popular method for authentication is the use of biometric data, but the uncertainty that arises due to the lack of uniqueness in biometrics has lead there to be a great deal of effort invested into multimodal biometrics. These multimodal biometric systems can give rise to large, distributed data sets that are used to decide the authenticity of a user. Bayesian model averaging (BMA) methodology has been used to allow experts to evaluate the reliability of decisions made in data mining applications. The use of decision tree (DT) models within the BMA methodology gives experts additional information on how decisions are made. In this paper we discuss how DT models within the BMA methodology can be used for authentication in multimodal biometric systems.
Citation:
Maple, C. and Schetinin, V.; (2006) 'Using a Bayesian averaging model for estimating the reliability of decisions in multimodal biometrics', Availability, Reliability and Security, ARES 2006. The First International Conference on , pp. 7
Publisher:
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
Issue Date:
2006
URI:
http://hdl.handle.net/10547/270799
DOI:
10.1109/ARES.2006.141
Additional Links:
http://ieeexplore.ieee.org/lpdocs/epic03/wrapper.htm?arnumber=1625407
Type:
Conference papers, meetings and proceedings
Language:
en
ISBN:
0769525679
Appears in Collections:
Centre for Research in Distributed Technologies (CREDIT)

Full metadata record

DC FieldValue Language
dc.contributor.authorMaple, Carstenen_GB
dc.contributor.authorSchetinin, Vitalyen_GB
dc.date.accessioned2013-03-01T11:02:23Z-
dc.date.available2013-03-01T11:02:23Z-
dc.date.issued2006-
dc.identifier.citationMaple, C. and Schetinin, V.; (2006) 'Using a Bayesian averaging model for estimating the reliability of decisions in multimodal biometrics', Availability, Reliability and Security, ARES 2006. The First International Conference on , pp. 7en_GB
dc.identifier.isbn0769525679-
dc.identifier.doi10.1109/ARES.2006.141-
dc.identifier.urihttp://hdl.handle.net/10547/270799-
dc.description.abstractThe issue of reliable authentication is of increasing importance in modern society. Corporations, businesses and individuals often wish to restrict access to logical or physical resources to those with relevant privileges. A popular method for authentication is the use of biometric data, but the uncertainty that arises due to the lack of uniqueness in biometrics has lead there to be a great deal of effort invested into multimodal biometrics. These multimodal biometric systems can give rise to large, distributed data sets that are used to decide the authenticity of a user. Bayesian model averaging (BMA) methodology has been used to allow experts to evaluate the reliability of decisions made in data mining applications. The use of decision tree (DT) models within the BMA methodology gives experts additional information on how decisions are made. In this paper we discuss how DT models within the BMA methodology can be used for authentication in multimodal biometric systems.en_GB
dc.language.isoenen
dc.publisherIEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INCen_GB
dc.relation.urlhttp://ieeexplore.ieee.org/lpdocs/epic03/wrapper.htm?arnumber=1625407en_GB
dc.subjectBayes procedureen_GB
dc.subjectmultimodal biometricsen_GB
dc.subjectbiometricsen_GB
dc.titleUsing a Bayesian averaging model for estimating the reliability of decisions in multimodal biometricsen
dc.typeConference papers, meetings and proceedingsen
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