TY - GEN
T1 - Cancelable iris biometrics and using error correcting codes to reduce variability in biometric data
AU - Kanade, Sanjay
AU - Petrovska-Delacrétaz, Dijana
AU - Dorizzi, Bernadette
PY - 2009/1/1
Y1 - 2009/1/1
N2 - With the increasing use of biometrics, more and more concerns are being raised about the privacy of the personal biometric data. Conventional biometric systems store biometric templates in a database. This may lead to the possibility of tracking personal information stored in one database by getting access to another database through cross-database matching. Moreover, biometric data are permanently associated with the user. Hence if stolen, they are lost permanently and become unusable in that system and possibly in all other systems based on that biometrics. In order to overcome this non-revocability of biometrics, we propose a two factor scheme to generate cancelable iris templates using iris-biometric and password. We employ a user specific shuffling key to shuffle the iris codes. Additionally, we introduce a novel way to use Error Correcting Codes (ECC) to reduce the variabilities in biometric data. The shuffling scheme increases the impostor Hamming distance leaving genuine Hamming distance intact while the ECC reduce the Hamming distance for genuine comparisons by a larger amount than for the impostor comparisons. This results in better separation between genuine and impostor users which improves the verification performance. The shuffling key is protected by a password which makes the system truly revocable. The biometric data is stored in a protected form which protects the privacy. The proposed scheme reduces the Equal Error Rate (EER) of the system by more than 90% (e.g., from 1.70% to 0.057% on the NIST-ICE database).
AB - With the increasing use of biometrics, more and more concerns are being raised about the privacy of the personal biometric data. Conventional biometric systems store biometric templates in a database. This may lead to the possibility of tracking personal information stored in one database by getting access to another database through cross-database matching. Moreover, biometric data are permanently associated with the user. Hence if stolen, they are lost permanently and become unusable in that system and possibly in all other systems based on that biometrics. In order to overcome this non-revocability of biometrics, we propose a two factor scheme to generate cancelable iris templates using iris-biometric and password. We employ a user specific shuffling key to shuffle the iris codes. Additionally, we introduce a novel way to use Error Correcting Codes (ECC) to reduce the variabilities in biometric data. The shuffling scheme increases the impostor Hamming distance leaving genuine Hamming distance intact while the ECC reduce the Hamming distance for genuine comparisons by a larger amount than for the impostor comparisons. This results in better separation between genuine and impostor users which improves the verification performance. The shuffling key is protected by a password which makes the system truly revocable. The biometric data is stored in a protected form which protects the privacy. The proposed scheme reduces the Equal Error Rate (EER) of the system by more than 90% (e.g., from 1.70% to 0.057% on the NIST-ICE database).
U2 - 10.1109/CVPRW.2009.5206646
DO - 10.1109/CVPRW.2009.5206646
M3 - Conference contribution
AN - SCOPUS:70450172561
SN - 9781424439935
T3 - 2009 IEEE Conference on Computer Vision and Pattern Recognition, CVPR 2009
SP - 120
EP - 127
BT - 2009 IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops, CVPR Workshops 2009
PB - IEEE Computer Society
T2 - 2009 IEEE Conference on Computer Vision and Pattern Recognition, CVPR 2009
Y2 - 20 June 2009 through 25 June 2009
ER -