Advancements in CNN-Based Iris Recognition: Enhancing Biometric Security and Authentication Systems

To improve biometric security and authentication, this study explores developments in CNN-based iris recognition systems. Using CNN architectures and sophisticated feature extraction, the research assesses the CNN-based system developed by IrisGuard. The system's 99.5% identification accuracy beats conventional approaches' 95% to 98% recognition accuracy, according to the results. The 150-millisecond authentication speed is optimized, which is faster than the 200–300 millisecond rates of earlier systems. Deployment expenses have been lowered to $400,000 from their previous range of $500,000 to $700,000. Furthermore, the system exhibits 98% accuracy resilience under a range of environmental circumstances and 95% regulatory compliance. The aforementioned outcomes highlight the system's exceptional capabilities in terms of precision, velocity, and economy, demonstrating its progress over traditional techniques and their usefulness in high-risk settings such as banking and healthcare.