• DocumentCode
    3004061
  • Title

    Cancelable iris biometrics and using Error Correcting Codes to reduce variability in biometric data

  • Author

    Kanade, Shantanu ; Petrovska-Delacretaz, Dijana ; Dorizzi, Bernadette

  • Author_Institution
    Dept. of Electron. & Phys., Inst. TELECOM: TELECOM & Manage. SudParis, Evry, France
  • fYear
    2009
  • fDate
    20-25 June 2009
  • Firstpage
    120
  • Lastpage
    127
  • Abstract
    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).
  • Keywords
    biometrics (access control); data privacy; database management systems; error correction codes; Hamming distance; biometric data; conventional biometric systems; cross-database matching; equal error rate; error correcting codes; iris biometrics; iris codes; iris templates; personal biometric data privacy; user specific shuffling key; Authentication; Bioinformatics; Biometrics; Data privacy; Databases; Error correction codes; Hamming distance; Iris; Protection; Testing;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Computer Vision and Pattern Recognition, 2009. CVPR 2009. IEEE Conference on
  • Conference_Location
    Miami, FL
  • ISSN
    1063-6919
  • Print_ISBN
    978-1-4244-3992-8
  • Type

    conf

  • DOI
    10.1109/CVPR.2009.5206646
  • Filename
    5206646