• Doppa Vasantha Kumari

In today world, digital security has become more critical than ever, relying on only passwords or single biometric methods are no longer sufficient. The multimodal biometric systems have many benefits over unimodal systems like lower error rates, higher accuracy and broader population coverage. In this we present a secure multimodal biometric authentication framework that combines multiple biometric traits-namely face, fingerprint, palm, iris, ear images. All these are included in a single robust system. Our approach employs Convolutional Neural Networks (CNN) for deep feature level fusion, which is followed by Kernel Linear Discriminant Analysis (KLDA). To strengthen data security and privacy, we integrate a deep hashing technique that converts the feature into secure, compact binary codes and ensures that the stored remains safe even in the event of data breach. The proposed system ensures template protection through cancellable biometrics, allowing secure storage and easy revocation of compromised biometric templates without risking user identity. The proposed system was evaluated using a benchmark multimodal biometric dataset, achieving an authentication accuracy of approximately 98%. The results clear demonstrate that combining multiple biometric inputs significantly enhances both the reliability and security of the authentication process compared to unimodal approaches. This project major objective is to establish a mechanism for fusing multimodal data from modalities like the face, finger print, palm, iris with deep hashing and biometric security, with a focus on structural data from these modalities.

Multimodal Biometrics, Kernel Linear Discriminant Analysis, Feature-level Fusion, Biometric security, privacy preservation, Template protection, cancellable Biometrics.

"SECURING MULTIMODAL BIOMETRICS", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.12, Issue 9, page no.e777-e784, September-2025, Available :http://www.jetir.org/papers/JETIR2509493.pdf

"SECURING MULTIMODAL BIOMETRICS", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.12, Issue 9, page no. ppe777-e784, September-2025, Available at : http://www.jetir.org/papers/JETIR2509493.pdf