Which feature of Cognitive Intelligence can separate statistically normal traffic from anomalous traffic?

Event classification is the specific Cognitive Intelligence feature that applies statistical modeling and machine learning to categorize network events, building behavioral baselines and flagging deviations that fall outside expected normal patterns. It is the core mechanism responsible for distinguishing statistically normal traffic from anomalous traffic within the Cognitive Intelligence framework.

Anomaly detection is a broad detection methodology category, not the specific named Cognitive Intelligence feature that performs the statistical separation of normal versus anomalous traffic.

Anomaly modeling refers to constructing reference models of anomalous behavior, not the classification process that actively separates normal traffic from anomalous traffic.

Trust modeling evaluates the trustworthiness of connections and entities in the network, which is a distinct function from statistically separating normal from anomalous traffic flows.