BIOMETRIC-INTEGRATED CLOUD FRAMEWORK FOR ROBUST SECURITY AND OPERATIONAL OPTIMIZATION

Abstract

The rapid adoption of cloud computing has revolutionized data storage, access, and management but has simultaneously introduced new vulnerabilities in authentication and system performance. Traditional authentication methods, such as passwords and tokens, are increasingly inadequate against sophisticated cyberattacks, leading to breaches, identity theft, and operational inefficiencies. To address these challenges, this study proposes a biometric-integrated cloud framework that leverages advanced biometric techniques— including fingerprint, facial recognition, and voice authentication—to ensure robust security while enhancing overall operational efficiency. By incorporating biometric data into the authentication pipeline, the system minimizes unauthorized access, strengthens identity verification, and reduces dependency on weak credentials. Additionally, the framework optimizes cloud operations by streamlining user access management and reducing overhead associated with conventional security protocols. Experimental evaluations demonstrate that the proposed model achieves a higher level of resilience against intrusion attempts, while simultaneously lowering authentication latency and improving resource utilization. This research highlights the transformative potential of biometric authentication in developing secure, reliable, and efficient cloud ecosystems suitable for both enterprise and individual applications