Biometric verification is a reliable approach that can be used to authenticate a person. Biometric authentication systems depend on unique human characteristics such as face, iris, fingerprint, gait, voice etc. to authenticate persons automatically. Biometrics varies from person to person and this is very sensitive data. This information should be kept safe, if not, severe security and privacy risks may occur. Biometric systems face some challenges like noise and non-universality in the process of establishing identity by using a single biometric trait. The noise in the data sensed from sensors may increase False Acceptance Rate (FAR) of the system where as non-universality may reduce Genuine Acceptance Rate (GAR). Because of this reason biometric systems that use single biometric trait provide less benefits in affording security. In this article, we device a Fused Multimodal system, which uses many biometric traits such as fingerprint, palmprint and voice etc. such that it may provide many advantages over uni-biometric systems such as, greater verification accuracy, larger feature space to accommodate more subjects and more security against spoofing. The newly proposed multimodal authentication system is primarily based on feature extraction using fingerprint, palm print, voice and key generation using RSA. MATLAB tool is used to carry out the experimentation. The performance of multimodal biometrics with RSA has significant improvement which has a GAR of 98% and FAR of 2%.

multi-modal biometrics, biometric fusion, fingerprint, palmprint, speech.

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