The identification of items, events, or observations that do not conform to an expected pattern or normal behavior in a dataset.
In insider threat detection, anomaly detection systems use statistical analysis and machine learning to identify unusual user behavior patterns that could indicate malicious activity. This includes detecting access to unusual files, working at odd hours, or data transfer patterns that deviate from normal behavior.
Mathematical techniques for collecting, analyzing, interpreting, and presenting data to identify patterns, trends, and relationships that inform security decision-making.
The use of statistical analysis and machine learning to identify patterns in user behavior and detect anomalies that may indicate security threats or policy violations.