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Biometric sensors rapid prototyping on field-programmable gate arrays

Published online by Cambridge University Press:  25 March 2015

Vincenzo Conti ,
Carmelo Militello ,
Filippo Sorbello  and
Salvatore Vitabile
Vincenzo Conti
Affiliation:
Facoltá di Ingegneria, e Architettura, Università degli Studi di Enna KORE, viale delle Olimpiadi, 94100, Enna, Italy e-mail: vincenzo.conti@unikore.it
Carmelo Militello
Affiliation:
Istituto di Bioimmagini e Fisiologia Molecolare – Consiglio Nazionale delle Ricerche (IBFM-CNR), UOS Cefalu’, C.da Pietrapollastra-Pisciotto – 90015 Cefalu’ (PA), Italy e-mail: carmelo.militello@ibfm.cnr.it
Filippo Sorbello
Affiliation:
Dipartimento di Ingegneria Chimica, Gestionale, Informatica, Meccanica, Universita’ degli Studi di Palermo, 90128 Palermo, Italy e-mail: filippo.sorbello@unipa.it
Salvatore Vitabile
Affiliation:
Dipartimento di Biopatalogia e Biotecnologie Mediche e Forensi, Universita’ degli Studi di Palermo, via del Vespro, 90127 Palermo, Italy e-mail: salvatore.vitabile@unipa.it
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Abstract

Biometric user authentication in large-scale distributed systems involves passive scanners and networked workstations and databases for user data acquisition, processing, and encryption. Unfortunately, traditional biometric authentication systems are prone to several attacks, such as Replay Attacks, Communication Attacks, and Database Attacks. Embedded biometric sensors overcome security limits of conventional software recognition systems, hiding its common attack points. The availability of mature reconfigurable hardware technology, such as field-programmable gate arrays, allows the developers to design and prototype the whole embedded biometric sensors. In this work, two strong and invasive biometric traits, such as fingerprint and iris, have been considered, analyzed, and combined in unimodal and multimodal biometric sensors. Biometric sensor performance has been evaluated using the well-known FVC2002, CASIA, and BATH databases.

Information

Type
Articles
Information
The Knowledge Engineering Review , Volume 30 , Issue 2: Intelligent Computing in Large–Scale Systems , March 2015 , pp. 201 - 219
Copyright
© Cambridge University Press, 2015 

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