How do anomaly detection policies in Microsoft Defender for Cloud Apps help identify unusual user behaviors?

Anomaly detection policies in Microsoft Defender for Cloud Apps are designed to enhance security by recognizing unusual patterns in user behavior. The correct answer emphasizes the use of a learned baseline, which involves establishing a norm based on typical user activities. This baseline is created by analyzing historical data and understanding what constitutes normal behavior for individual users or groups.

When current user activities are compared against this established baseline, the system can efficiently identify deviations. For example, if a user who typically logs in from a specific geographic location suddenly accesses the system from an entirely different region at unusual hours, this anomaly would trigger alerts. The insights gained through this method enable organizations to proactively address potentially malicious activities before they escalate into security incidents.

Other methods for identifying unusual user behavior, such as manually reporting deviations or sending daily summaries for review, are less efficient and could lead to delays in detecting real-time threats. Blocking all activities that do not align with a strict workflow would hinder user productivity and may not be practical in dynamic work environments. Thus, the anomaly detection method provides a more adaptive and effective approach to enhancing security posture.