Title :
Revocable fingerprint biotokens: accuracy and security analysis
Author :
Boult, Terrance E. ; Scheirer, Walter J. ; Woodworth, R.
Author_Institution :
VAST Lab, Univ. of Colorado at Colorado Springs, Colorado Springs, CO, USA
Abstract :
This paper reviews the biometric dilemma, the pending threat that may limit the long-term value of biometrics in security applications. Unlike passwords, if a biometric database is ever compromised or improperly shared, the underlying biometric data cannot be changed. The concept of revocable or cancelable biometric-based identity tokens (biotokens), if properly implemented, can provide significant enhancements in both privacy and security and address the biometric dilemma. The key to effective revocable biotokens is the need to support the highly accurate approximate matching needed in any biometric system as well as protecting privacy/security of the underlying data. We briefly review prior work and show why it is insufficient in both accuracy and security. This paper adapts a recently introduced approach that separates each datum into two fields, one of which is encoded and one which is left to support the approximate matching. Previously applied to faces, this paper uses this approach to enhance an existing fingerprint system. Unlike previous work in privacy-enhanced biometrics, our approach improves the accuracy of the underlying svstem! The security analysis of these biotokens includes addressing the critical issue of protection of small fields. The resulting algorithm is tested on three different fingerprint verification challenge datasets and shows an average decrease in the Equal Error Rate of over 30% - providing improved security and improved privacy.
Keywords :
data privacy; fingerprint identification; biometric database; biometric-based identity tokens; equal error rate; fingerprint verification; privacy-enhanced biometrics; revocable fingerprint biotokens; security analysis; Biometrics; Biosensors; Data privacy; Data security; Databases; Fingerprint recognition; Government; Optical losses; Springs; Testing;
Conference_Titel :
Computer Vision and Pattern Recognition, 2007. CVPR '07. IEEE Conference on
Conference_Location :
Minneapolis, MN
Print_ISBN :
1-4244-1179-3
DOI :
10.1109/CVPR.2007.383110