An Enhanced Secure Framework for Detecting and Rectifying Unauthorized Access in Cloud Computing Environments Using the Elliptic Curve Digital Signature Algorithm

While cloud computing environments offer significant advantages, they also pose serious security challenges, especially in the detection and rectification of unauthorized access. Traditional methods, including Role-Based Access Control (RBAC), Multi-Factor Authentication (MFA), and Advanced Encryption Standard (AES), are widely used but suffer from a number of drawbacks, including high computational cost, scalability issues, and vulnerability to modern cyber-attacks. This reduces their effectiveness in ensuring real-time security and efficient access management in cloud systems. The aforementioned limitations are addressed by the proposed Enhanced Secure Detection and Rectification Framework (E-SDRF), which is based on the Elliptic Curve Digital Signature Algorithm (ECDSA) method. By employing this method, cloud security is enhanced through the implementation of more robust authentication, faster detection, and efficient rectification against unauthorized access. The proposed framework has the potential to reduce computational overhead while increasing accuracy and speed in the cloud environment. The experimental setup for analysis demonstrates significant improvements in four key performance areas: a 0.25% increase in detection accuracy, a 0.30% reduction in rectification time, a 0.20% improvement in computational efficiency, and a 0.15% reduction in false positives. The findings indicate the efficacy of the proposed E-SDRF in addressing security challenges in dynamic and large-scale cloud computing infrastructures, rendering it highly suitable for next-generation cloud environments.