Mathematical techniques for collecting, analyzing, interpreting, and presenting data to identify patterns, trends, and relationships that inform security decision-making.
Statistical analysis in insider threat detection involves techniques such as regression analysis, correlation analysis, time series analysis, and clustering to identify meaningful patterns in user behavior data. These methods help distinguish between normal variations and suspicious activities, calculate confidence intervals for risk assessments, and validate the effectiveness of security controls. Advanced statistical models can predict likelihood of insider threat incidents based on historical patterns and current behavioral indicators.