A novel hand reconstruction approach and its application to vulnerability assessment

Gómez-Barrero, Marta; Galbally Herrero, Javier; Morales Moreno, Aythami; Ferrer, Miguel Ángel; Fiérrez Aguilar, Julián; Ortega-García, Javier

UAM_Biblioteca

Author

Gómez-Barrero, Marta; Galbally Herrero, Javier; Morales Moreno, Aythami

; Ferrer, Miguel Ángel; Fiérrez Aguilar, Julián

; Ortega-García, Javier

Entity

UAM. Departamento de Tecnología Electrónica y de las Comunicaciones

Publisher

Elsevier B.V.

Date

2014-06-01

Citation

Information Sciences. 238 (2014): 103-121

ISSN

0020-0255 (print); 1872-6291 (online)

DOI

10.1016/j.ins.2013.06.015

Funded by

This work has been partially supported by projects Contexts (S2009/TIC-1485) from CAM, Bio-Challenge (TEC2009-11186), BIOSINT (TEC2012-38630-C04-02) and Bio-Shield (TEC2012-34881) from Spanish MINECO, TABULA RASA (FP7-ICT-257289) and BEAT (FP7-SEC-284989) from EU, and Cátedra UAM-Telefónica. Marta Gomez-Barrero is supported by a FPU Fellowship from Spanish MECD.

Project

info:eu-repo/grantAgreement/EC/FP7/257289; info:eu-repo/grantAgreement/EC/FP7/284989; Comunidad de Madrid. S2009/TIC-1485/CONTEXTS

Editor's Version

http://dx.doi.org/10.1016/j.ins.2013.06.015

Subjects

Biometric system; Hand recognition; Hand reconstruction; Security; Vulnerability; Telecomunicaciones

URI

http://hdl.handle.net/10486/662092

Note

This is the author’s version of a work that was accepted for publication in Information Sciences. Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document. Changes may have been made to this work since it was submitted for publication. A definitive version was subsequently published in Information Sciences, 238 (2014) DOI: 10.1016/j.ins.2013.06.015

Rights

Esta obra está bajo una licencia de Creative Commons Reconocimiento-NoComercial-SinObraDerivada 4.0 Internacional.

Abstract

The present work proposes a novel probabilistic method to reconstruct a hand shape image from its template. We analyse the degree of similarity between the reconstructed images and the original samples in order to determine whether the synthetic hands are able to deceive hand recognition systems. This analysis is made through the estimation of the success chances of an attack carried out with the synthetic samples against an independent system. The experimental results show that there is a high chance of breaking a hand recognition system using this approach. Furthermore, since it is a probabilistic method, several synthetic images can be generated from each original sample, which increases the success chances of the attack.

Show full item record