Multimodal Biometric Fusion System

With the increased demand in the security and privacy concerns for authentication, this research gives a solution with a high standard of privacy with a multimodal authentication system with two unique features in a human which include a human ear and a human face. The primary objectives of this system are to empower users with greater security, enhance their data protection, and establish a seamless framework for users to use the application with their specific applications. This multimodal biometric fusion system is interconnected through various deep learning algorithms, ensuring continuous data storage and the identification of stored data in a dataset. The key advantages of the system include enhanced security, improved accuracy and reliability, reduced vulnerability to spoofing, diversity and inclusivity, robustness to environmental factors, redundancy and fault tolerance, userfriendly experience, flexibility in deployment, and continuous innovation. However, the successful implementation of this system necessitates meticulous attention to security, privacy, and regulatory compliance. In summary, this proposed multimodal biometric authentication system gives the solution to the authentication system with 99.95% accuracy with the hybrid combination of human and ear images. The fusion techniques of human and ear gives good solution for multifactor authentication with increased security compared to single factor authentication system and other multifactor systems