A security analyst is reviewing alerts from a system that profiles user login times, data access patterns, and network traffic. The system flagged an administrator account that logged in at 3:00 AM from an unfamiliar IP address and attempted to access a sensitive financial database, which is outside the administrator's usual job responsibilities. This activity deviates significantly from the established baseline for this user. Which of the following security concepts is BEST demonstrated in this scenario?
User Behavior Analytics (UBA) is the concept being demonstrated. UBA systems are designed to learn normal user behavior by establishing a baseline of activities, such as typical login times, data access patterns, and locations. When an activity, like logging in at an unusual time from an unknown IP and accessing atypical resources, deviates from this baseline, the UBA system generates an alert for a potential security threat, such as a compromised account or an insider threat. Honeypots are decoy systems, vulnerability scanning proactively looks for weaknesses, and threat intelligence feeds provide external data on threats; none of these describe the internal, behavior-focused monitoring shown in the scenario.
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How does User Behavior Analytics (UBA) work in detecting anomalies?
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What types of data does UBA rely on to detect abnormal behavior?
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How does UBA differ from traditional security monitoring tools?