MVRAF framework quantifies CVE risks via weighted CVSS aggregation, statistical correlation analysis, and empirical cumulative distributions, classifying 46.2% of network-based vulnerabilities as high-risk with strong CIA-severity links.
Machine learning in cybersecurity: A comprehen- sive review of threat detection, prevention, and response strategies
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Policy-Driven Vulnerability Risk Quantification framework for Large-Scale Cloud Infrastructure Data Security
MVRAF framework quantifies CVE risks via weighted CVSS aggregation, statistical correlation analysis, and empirical cumulative distributions, classifying 46.2% of network-based vulnerabilities as high-risk with strong CIA-severity links.