TY - JOUR
T1 - A two-dimensional random projected minutiae vicinity decomposition-based cancellable fingerprint template
AU - Jin, Zhe
AU - Goi, Bok Min
AU - Teoh, Andrew
AU - Tay, Yong Haur
N1 - Publisher Copyright:
© 2013 John Wiley & Sons, Ltd.
Copyright:
Copyright 2020 Elsevier B.V., All rights reserved.
PY - 2014/11/1
Y1 - 2014/11/1
N2 - With the massive deployment of biometric applications, protecting the biometric template has attracted great attention because of the privacy issue. Although many proposals on protecting biometric template have been reported in literature, design a method simultaneously satisfying four criteria, that is performance, non-invertibility, cancellability, and diversity still remains unsolved. In this paper, we proposed a two-dimensional random projected minutiae vicinity decomposition (MVD) technique to secure minutiae-based fingerprint template. Minutiae vicinity is first formed from a set of fingerprint minutiae and further used to generate a set of local features, namely MVD features; then, a random matrix derived from user-specific token is used to project MVD features for the concealment of the topology of MVD. Comprehensive experiments on fingerprint verification competition datasets are carried out, and the lowest equal error rate obtained in the stolen-token scenario is 3.07% and 1.02% for fingerprint verification competition 2002 database 1 and database 2, respectively. Besides, detail analyses on the irreversibility, cancellability, template size, and computational cost have been carried out.
AB - With the massive deployment of biometric applications, protecting the biometric template has attracted great attention because of the privacy issue. Although many proposals on protecting biometric template have been reported in literature, design a method simultaneously satisfying four criteria, that is performance, non-invertibility, cancellability, and diversity still remains unsolved. In this paper, we proposed a two-dimensional random projected minutiae vicinity decomposition (MVD) technique to secure minutiae-based fingerprint template. Minutiae vicinity is first formed from a set of fingerprint minutiae and further used to generate a set of local features, namely MVD features; then, a random matrix derived from user-specific token is used to project MVD features for the concealment of the topology of MVD. Comprehensive experiments on fingerprint verification competition datasets are carried out, and the lowest equal error rate obtained in the stolen-token scenario is 3.07% and 1.02% for fingerprint verification competition 2002 database 1 and database 2, respectively. Besides, detail analyses on the irreversibility, cancellability, template size, and computational cost have been carried out.
KW - Fingerprint template protection
KW - Minutiae vicinity decomposition
KW - Two-dimensional random projection
UR - http://www.scopus.com/inward/record.url?scp=84896502577&partnerID=8YFLogxK
U2 - 10.1002/sec.865
DO - 10.1002/sec.865
M3 - Article
AN - SCOPUS:84896502577
SN - 1939-0114
VL - 7
SP - 1691
EP - 1701
JO - Security and Communication Networks
JF - Security and Communication Networks
IS - 11
ER -