Proactive Cloud Risk Assessment for Enterprise Security Using Machine Learning and Regulatory Compliance Intelligence

Abstract

The increasing adoption of cloud computing has intensified enterprise security challenges associated with data confidentiality, access management, vulnerability exposure, regulatory compliance, and evolving cyber threats. Traditional risk assessment approaches frequently depend on periodic audits, predefined security rules, and manual compliance reviews, limiting their ability to identify emerging risks and continuously evaluate regulatory obligations. This study proposes a proactive cloud risk assessment framework that integrates machine learning with regulatory compliance intelligence to support enterprise security management. The framework combines cloud configuration records, identity and access management logs, vulnerability assessments, security events, asset criticality, and regulatory control requirements to identify security weaknesses and estimate risk levels. Machine learning algorithms, including Random Forest, XGBoost, Support Vector Machine, and anomaly detection models, are considered for risk prediction, threat prioritization, and identification of noncompliant cloud configurations. A regulatory intelligence component maps relevant security observations to applicable control requirements derived from frameworks such as ISO/IEC 27001, the NIST Cybersecurity Framework, and the CIS Critical Security Controls. The proposed methodology incorporates data preprocessing, feature engineering, predictive modeling, compliance mapping, and risk-based remediation prioritization. Evaluation considers precision, recall, F1-score, false-positive rate, risk-ranking effectiveness, and compliance mapping accuracy. The framework aims to improve continuous risk visibility, accelerate remediation, strengthen audit readiness, and support evidence-based security decisions. By combining predictive analytics with regulatory context, the study establishes a foundation for adaptive, transparent, and compliance-aware enterprise cloud security management.