A NOVEL APPROACH TO GENERATE A SECURED CRYPTOGRAPHIC KEY FROM MULTIMODAL BIOMETRICS: FEATURE LEVEL FUSION OF FINGERPRINT AND IRIS

Abstract

Human users have a tough time remembering long cryptographic keys. Therefore, researchers, for a long, period of time have been exploratory ways to utilize biometric features of the user instead of a memorable password or passphrase, in an effort to create strong and repeatable cryptographic keys. Our aim is to incorporate the volatility of the user’s biometric features into the generated key, so as to make the key unguessable to an attacker lacking significant knowledge of the user’s biometrics. We go one step further trying to incorporate multiple biometric modalities into cryptographic ke yg eneration so as to provide better security. In this article, we propose an efficient approach based on multimodal biometrics (Iris and fingerprint) for generation of secure cryptographic key. The proposed approach is composed of three modules namely, (i) Feature extraction, (ii) Multimodal biometric template generation and (iii) Cryptographic ke yg eneration. Initially, the features, minutiae points and texture properties are extracted from the fingerprint and iris images respectively. Subsequently, the extracted features are fused together at the feature level to construct the multi-biometric template. Finally, a 256-bit secure cryptographic key is generated from the multi-biometric template. For experimentation, we have employed the fingerprint images obtained from publicly available sources and the iris images from CASIA Iris Database. The experimental results illustrate the effectiveness of the proposed approach.