What is it?
User Behaviour Analytics (UBA) is the process of tracking, analysing, and detecting patterns in user activities to identify potential threats. By establishing behavioural baselines and recognising deviations, UBA helps organisations detect insider threats, compromised credentials, and policy violations before they escalate into major incidents.
What could happen?
Without UBA, security teams rely on static rules and external threat intelligence, which may fail to detect subtle or sophisticated attacks originating from within. Anomalous activities like unauthorised access to sensitive data, off-hours logins, or excessive file downloads might go unnoticed, leading to data breaches, fraud, or operational downtime.
What to do about it?
Foundational: Deploy logging and monitoring tools to track user activities, such as login attempts, file access, and privilege escalations. Define baseline behavioural patterns to compare against abnormal activity.
Outcome: Establishes a foundational layer for monitoring user behaviour.
Enhanced: Implement advanced UBA tools with machine learning algorithms to detect behavioural anomalies in real-time. Integrate alerts with existing SIEM solutions to streamline threat detection.
Outcome: Improves detection accuracy and reduces false positives, enabling faster response.
Comprehensive: Leverage UBA to build a dynamic risk scoring system for users, combining contextual data (e.g., geolocation, time of access) with historical behaviour. Integrate this system into broader threat intelligence platforms for proactive risk management.
Outcome: Provides a proactive, adaptive approach to identifying and mitigating insider threats and unusual user activity.
