Cloud-Based Biometric Security Solutions with AI for Secure Healthcare Data Sharing

Healthcare data security solutions are needed that will be able to withstand the growth of cloud computing in storing and sharing healthcare records. With traditional authentication mechanisms such as passwords and single-modal biometrics, cyber threats and unauthorized access are a reality. The study provides a biometric security system for the cloud by using artificial intelligence that integrates deep learning for anomaly detection and homomorphic encryption with multimodal biometrics, such as voice authentication, face recognition, and fingerprints. In this proposed system, the maintenance of compliance with such regulatory requirements as GDPR and HIPAA guarantees safe and easy access to healthcare data. With the instant detection of suspicious access patterns, AI-driven anomaly detection enhances security, and blockchain technology ensures immutable recording for auditability. Edge computing further optimizes the authentication response time for efficient system operation. Results demonstrate the system with high authentication accuracy, quick reaction time, and robust resistance to cyber-attacks. This solution is based on addressing the important need of better security for current healthcare systems, thus providing safe, scalable, and privacy-preserving healthcare data exchange.