Enhancing Biometric Security: A Framework for Detecting and Preventing False Identification

Abstract

Biometrics is a technological system that utilizes data to differentiate one individual from another. The biometric framework can be used by government and private organizations for security purposes. This software-based technology helps to look at an individual's data if it is genuine or fake. The study suggested a framework; its goal is to strengthen the development and acceptance of the biometric system. The function of this system is to reduce the applied effort to identify and recognize the quality of the image in less time. This study utilizes three data applications: iris, fingerprint, and face recognition. The approach proposed by the survey uses different features of the images to determine the difference between the original image and the considered sample image. It gives efficient protection against different spoofing attacks. Simulation results show that the high-quality detection application has an average peak signal-to-noise ratio (PNSR) of 89.77. Further, the proposed model effectively detects false biometric identification.