A statistical model of normal user behavior patterns established over time, used to detect anomalies that may indicate security threats or policy violations.
Behavioral baselines are created by analyzing user activities, access patterns, data usage, and system interactions during normal operations. Machine learning algorithms identify what constitutes typical behavior for each user or role, enabling the detection of deviations that could indicate compromise, insider threats, or other security incidents.
A cybersecurity process that takes note of the normal conduct of users and entities within a network and identifies any anomalous behavior that could indicate a security threat.
The identification of items, events, or observations that do not conform to an expected pattern or normal behavior in a dataset.
The systematic observation and analysis of user behavior patterns to identify potential security risks or policy violations.