Secure Multi-Modal Biometric Authentication Using Deep Learning
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Abstract
Traditional authentication methods are vulnerable to security breaches. This paper introduces a multi-modal biometric authentication system that combines facial recognition, fingerprint scanning, and voice recognition using deep learning techniques. The proposed system enhances security by integrating multiple biometric modalities, reducing the risk of spoofing attacks. Experimental results show improved accuracy and robustness compared to single-modality systems. The approach is suitable for high-security applications in banking and government sectors.
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References
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