Abstract
Biometric analysis for identifying verification is becoming a widespread reality. It is a very challenging and tedious task to develop a biometric template protection scheme which is anonymous, revocable and noninvertible while maintaining decent performance. Cancellable biometrics is one of the best methods used to resolve this problem. In this paper, a new method called as BioHashing which follows the technique of cancellable biometrics in the fingerprint domain is proposed. This proposed method does not require the re-alignment of fingerprints as all the minutiae are translated into a pre-defined two dimensional space based on a reference minutia. After that, the proposed Biohashing method is used to enforce the one-way property (non-invertibility) of the biometric template. The proposed approach is very much resistant to minor translation error and rotation distortion. An Equal Error Rates (EER) of less than 1% is achieved in this approach and performance of the approach is also significant.
Highlights
Biometric approaches for the identification of the authorized users are becoming a widespread reality
BioHashing technique was introduced as a form of cancellable or replaceable biometrics, in which a set of user-specific random numbers are integrated with biometric features to address the problem of privacy and security
This paper provides a statistical model of the relationship among the enrolment biometric and the biometric measurement considering in the process of authentication
Summary
Biometric approaches for the identification of the authorized users are becoming a widespread reality. BioHashing technique was introduced as a form of cancellable or replaceable biometrics, in which a set of user-specific random numbers are integrated with biometric features to address the problem of privacy and security. In order to solve the problem of high false rejection, a novel two-factor authenticator technique is proposed which is based on iteration of the inner products between tokenized pseudo-random number and the user specific fingerprint features. This proposed method provides a set of user specific compact codes which is named as Biohash code. BioHashing approach achieved a zero EER rate based on the impractical hidden assumption of no stealing of the Hash key
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