Risk-Based Authentication for Enhanced Cloud Security: A Context-Aware Approach
Abstract
Authentication remains a critical component of cloud security, yet static authentication mechanisms are often inadequate against sophisticated attacks. This paper proposes a risk-based authentication framework that dynamically adjusts authentication requirements based on contextual factors such as user behavior, location, and device characteristics. The framework leverages machine learning to calculate risk scores in real-time and determine the appropriate level of authentication. High-risk scenarios trigger multi-factor authentication (MFA) or additional identity verification steps. Experimental results demonstrate that the proposed system improves security without compromising user experience by balancing risk and convenience. The study emphasizes the importance of context-aware security mechanisms in modern cloud environments.
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