Mitigating Security Threats in Cloud Biometric Authentication Through a Privacy Preserving Multi Modal Biometric Cryptography Based System for Secure Identification

The research introduces a secure system using privacy-preserving multi-modal biometric cryptography to confront major security flaws in biometric authentication over the cloud. The system uses both fingerprint and facial recognition along with strong cryptography to guard biometric data as it is sent and kept. Spreading, repeating and tampering with the system using false identities are mitigated by liveness checks, encrypting templates, using valid authentication keys during each use and through asymmetrical digital signatures. Simulations of over 1,000 authentications found that the FAR fell from 4.2% to 0.6% and the FRR reduced from 5.8% to 1.2%. In addition, the security system dealt with 95% of fake attempts and correctly agreed with genuine users in 99.1% of cases. Having encryption and authentication methods in place greatly cut the likelihood of man-in-the-middle attacks by 98%. The results suggest that the proposed system enhances security, provides privacy and maintains excellent user authentication rates in cloud biometric systems.