Personal Authentication System Based on Iris Recognition and Digital Signature Technology
Keywords:Multimodal iris recognition, Convolutional Neural Network (CNN), Biometric Signatures, Rivest–Shamir–Adleman (RSA) algorithm
Authentication based on biometrics is being used to prevent physical access to high-security institutions. Recently, due to the rapid rise of information system technologies, biometrics is now being used in applications to access databases and commercial workflow systems. These applications need to implement measures to counter security threats. Many developers are exploring and developing novel authentication techniques to prevent these attacks. However, the most challenging problem is how to keep biometric data while maintaining the functional performance of identity verification systems. This paper presents a biometrics-based personal authentication system in which a smart card, a Public Key Infrastructure (PKI), and iris verification technologies are combined. Raspberry Pi 4 Model B+ is used as the core of hardware components with an IR Camera. Following that idea, we designed an optimal image processing algorithm in OpenCV, Python, Keras, and sci-kit learn libraries for feature extraction and recognition is chosen for application development in this project. After training, the implemented system gives an accuracy of (97% and 100%) for the left and right (NTU) iris datasets. Later, the person verification based on the iris feature is performed to verify the claimed identity and examine the system authentication. For the NTU iris dataset, the time of key generation, Signature, and Verification is 5.17sec,0.288, and 0.056, respectively. This work offers the realistic architecture to implement identity-based cryptography with biometrics using the Rivest–Shamir–Adleman (RSA) algorithm.