To detect outliers, which Anomaly Detection Engine rule tests events or flows for volume changes that occur in regular patterns?

To detect outliers, which Anomaly Detection Engine rule tests events or flows for volume changes that occur in regular patterns?
A . Behavioral rules
B . Threshold rules
C . Anomaly rules
D . Building block rules

View Answer

Answer: C

Explanation:

In IBM QRadar SIEM V7.5, Anomaly Detection Engine rules that test events or flows for volume changes occurring in regular patterns are known as Anomaly Rules.

Here’s how they function:

Detection: Anomaly rules are designed to identify deviations from normal behavior by analyzing patterns in the data.

Volume Changes: These rules specifically look for unusual increases or decreases in event or flow volumes that might indicate potential security incidents.

Regular Patterns: By understanding regular patterns in network traffic and event logs, anomaly rules can highlight significant outliers that warrant further investigation.

Reference

The functionality and configuration of anomaly rules are covered extensively in the IBM QRadar SIEM administration guide, providing administrators with the tools to effectively detect and respond to abnormal network activities.