Robust Authentication System with Privacy Preservation of Biometrics

IoT-based multi-biometric system is a blend of multiple biometric templates that can be used for user authentication/verification using sensors. The leakage the trait information may cause critical privacy and security issues. It expected to protect details individuals through irreversibility, unlinkability, renewability in authentication system. This study presents robust with secure template protection techniques based on discrete cosine transform feature transformation Lagrange’s interpolation-based image transformation. Three traits namely iris, fingerprint, palm print are recorded sensors validate proposed fusion all giving an average 95.42% genuine acceptance rate 4.57% false rejection rate. Despite any number authentication, keep size final storage requirement as 8 X 8, which achieves constant space complexity (O(1)). stored not linked original templates; it irreversible renewable new enrolment same individual will produce every time. Overall, technique provides high accuracy, database, preservation traits.