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The findings demonstrate the effectiveness of the graph-based methods in providing high-quality behavioral dependencies, with better accuracy and fewer false alarms and greater explainability in real-life insider risk monitoring.
This study suggests a Secure Behavioral Zero-Trust Access Control Framework (SB-ZTAC), which establishes the integration of 3 modules in one unified framework: Machine learning based behavioral analytics, Zero-trust policy enforcement, and Blockchain based auditing.
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