Built-in Analytics and Machine Learning
Leverage Sentinel's machine learning and advanced analytics capabilities for threat detection.
Sentinel incorporates machine learning models that identify anomalies and patterns invisible to traditional rule-based detection. These analytics include user and entity behavior analytics (UEBA) that establish baselines for normal user activity and flag deviations, anomaly detection that identifies unusual login patterns or resource access, and threat intelligence correlation that matches observed indicators against known malicious entities. Machine learning is particularly effective for identity threats because normal behavior varies widely by user role and context—ML can detect subtle deviations that would require thousands of manual rules. Security professionals should understand what models are available, how they're trained on organizational data, how…
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