Abstract
Biometrics-based authentication is playing an attractive and potential approach nowadays. However, the end-users do not feel comfortable to use it once the performance and security are not ensured. Fuzzy vault is one of the most popular methods for biometric template security. It binds a key with the biometric template and obtains the helper data. However, the main problem of fuzzy vault is that it is unable to guarantee the revocability property. In addition, most of the fuzzy vault schemes are performed on two biometrics modalities, fingerprints and iris. In previous works, authors suggested some cancelable transformations attached to a fuzzy vault scheme to overcome these weaknesses. However, the computational cost of these proposals was quite large. In this paper, we present a new hybrid scheme of fuzzy vault and periodic function-based feature transformation for biometric template protection. Our transformation is not only simpler but also suitable for many kinds of biometrics modalities. The newly proposed fuzzy vault scheme guarantees the revocability property with an acceptable error rate.
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Le, T.T.B., Dang, T.K., Truong, Q.C., Nguyen, T.A.T. (2014). Protecting Biometric Features by Periodic Function-Based Transformation and Fuzzy Vault. In: Hameurlain, A., Küng, J., Wagner, R., Dang, T., Thoai, N. (eds) Transactions on Large-Scale Data- and Knowledge-Centered Systems XVI. Lecture Notes in Computer Science(), vol 8960. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-662-45947-8_5
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DOI: https://doi.org/10.1007/978-3-662-45947-8_5
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