Leveraging AI and Machine Learning to Enhance Security Compliance in Cloud Infrastructures
Keywords:
infrastructures, essential, remediation, identifyingAbstract
This paper investigates the application of artificial intelligence (AI) and machine learning (ML) to enhance security compliance within Oracle Cloud Infrastructure (OCI) SaaS services. By implementing an AI-driven compliance monitoring system, this study aims to improve real-time anomaly detection, predictive compliance risk scoring, and remediation processes. The findings indicate that AI-based compliance monitoring increased overall compliance scores by 25%, with a notable 40% reduction in mean remediation time compared to traditional methods. Additionally, anomaly detection models achieved a false-positive rate of 4%, significantly lower than the industry average. The predictive risk scoring model reached an accuracy of 90%, successfully identifying high-risk compliance categories, such as configuration management and access control. These results suggest that AI and ML can offer substantial benefits in automating and improving cloud security compliance, making them essential tools for modern SaaS infrastructures.
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