What it is
User Behavior Analytics (UBA) applies data analytics and machine learning to monitor user activity and detect deviations from normal behavior. It establishes behavioral baselines for users�such as login times, access patterns, or file activity�and flags actions that deviate significantly from the norm.
UBA systems integrate with SIEMs and identity providers to correlate data across multiple systems. For instance, a user logging in from two different countries within minutes may trigger an alert for potential credential compromise.
Why it matters
Traditional signature-based detection cannot identify insider threats or subtle misuse of legitimate accounts. UBA adds a behavioral dimension to security monitoring, allowing organizations to detect sophisticated threats early, including account takeovers and privilege abuse.
How to reduce risk
- Feed UBA tools with diverse data sources such as authentication logs, endpoints, and cloud applications.
- Define clear escalation procedures for behavioral anomalies.
- Combine UBA with identity governance for stronger access control.
- Continuously refine baselines to adapt to evolving workflows.
- Use anonymization to preserve user privacy during monitoring.