Context-Driven Threat Analysis and Intelligent Security Enforcement for Distributed Enterprise Cloud Environments

Abstract

Enterprise cloud infrastructure has become increasingly complex due to the widespread adoption of multi-cloud environments, containerized applications, distributed workloads, and dynamic resource provisioning. These developments introduce security challenges that traditional vulnerability assessment approaches cannot adequately address because they often evaluate threats independently of operational context. This study proposes a context-aware security assessment framework that integrates risk scoring, continuous monitoring, threat intelligence, and automated remediation to improve enterprise cloud security. The proposed framework evaluates security risks by considering vulnerability severity, asset criticality, exposure to external networks, identity permissions, threat activity, configuration weaknesses, and potential business impact. A context-sensitive risk scoring mechanism prioritizes security issues according to their likelihood and consequences rather than relying exclusively on predefined severity ratings. Automated remediation mechanisms are incorporated to address recurring misconfigurations, excessive permissions, exposed resources, and policy violations while maintaining operational continuity through approval workflows and rollback capabilities. The research methodology combines a conceptual framework design, simulated cloud security scenarios, quantitative risk evaluation, and comparative performance analysis. Evaluation criteria include detection accuracy, remediation time, false-positive rate, risk reduction, and operational overhead. The proposed approach aims to improve the efficiency of security operations, reduce the exposure window of critical assets, and support consistent security governance across heterogeneous cloud environments. The study contributes a structured approach for integrating contextual risk intelligence with controlled, scalable, and auditable security remediation.