Unified Enterprise Cloud Risk Intelligence through Cross-Platform Threat Analysis and Security Policy Optimization

Abstract

The rapid adoption of cloud computing, hybrid infrastructure, and multi-cloud environments has increased the complexity of enterprise cybersecurity risk management. Organizations increasingly depend on distributed cloud platforms, interconnected applications, identity management systems, and third-party services, creating fragmented security visibility and expanding the attack surface. This study explores a unified enterprise cloud risk intelligence framework that integrates cross-platform threat analysis, security data correlation, risk prioritization, and security policy optimization. The proposed approach combines threat intelligence, security event monitoring, vulnerability assessment, identity and access management analysis, and compliance evaluation to establish a consolidated understanding of enterprise cloud risks. It emphasizes the normalization of heterogeneous security data, correlation of threat indicators across cloud environments, contextual risk scoring, and adaptive policy recommendations. The research methodology adopts a design-oriented analytical approach supported by comparative assessment, scenario-based evaluation, and quantitative performance indicators. Key evaluation dimensions include threat detection accuracy, false-positive rate, incident response time, policy compliance, and risk mitigation effectiveness. The framework aims to improve organizational visibility, reduce redundant security alerts, and support consistent enforcement of security controls across cloud providers. By connecting threat intelligence with policy optimization, the proposed model provides a structured foundation for proactive, scalable, and risk-informed cloud security management. The study contributes to enterprise cybersecurity research by presenting an integrated approach to cloud risk intelligence that supports operational resilience, regulatory alignment, and continuous security improvement.