Security analysis of password hardened multimodal biometric fuzzy vault with combined feature points extracted from fingerprint, iris and retina for high security applications

Abstract

Establishing the identity of an individual is very crucial in the present times. Biometric authentication has proved itself superior compared to the traditional password based authentication in many respects. Nevertheless, biometric systems are prone to a variety of attacks. The stored biometric template attack is the most severe of all the attacks. Hence providing security to this form is of prime importance. Moreover, biometric templates may reveal private information about diseases and disorders of a person. Biometric templates cannot be reissued on spoofing. Therefore, apart from security; biometric templates should be imparted with revocability. This work secures the multimodal biometric templates by the crypto biometric fuzzy vault framework. Fuzzy vault suffers from certain limitations like non-revocability, cross matching and lack of diversity. The fuzzy vault is hardened with a password to overcome these limitations. Multi biometric systems are more resistive towards spoof attacks compared to their unimodal counterparts. This work extracts feature points from three different biometric modalities namely fingerprint, iris and retina. The password-hardened revocable templates are then secured in a multimodal biometric fuzzy vault. Passwords act as an additional layer of security apart from providing revocability. Combining the retina with the iris improves user convenience as both the capturing devices can be mounted in a single device. Users having problems with eye biometrics can utilize fingerprint and vice versa. The security of the multimodal password hardened fuzzy vault is measured using min-entropy. The number of computations required to compromise the vault by brute force attack is also calculated.