A security operations center (SOC) is concerned about sophisticated insider threats and zero-day attacks that might not trigger their existing signature-based security tools. The SOC has recently deployed a new system that establishes a baseline of normal activity for each user and network device. An analyst receives an alert from this system about an accounting user who, despite normally working 9-to-5, has just accessed the customer database at 3 AM and is downloading an unusually large volume of records. Which security solution is BEST suited for generating this type of context-rich, behavior-based alert?
The correct answer is User and Entity Behavior Analytics (UEBA). UEBA solutions are specifically designed to address this type of threat by first establishing a baseline of normal behavior for users and entities (e.g., servers, devices) within a network. Using machine learning and advanced analytics, UEBA systems then monitor for deviations from this baseline, such as unusual login times, abnormal data access patterns, or large data transfers. This makes UEBA particularly effective at detecting insider threats and compromised accounts, which might not be caught by signature-based tools like an Intrusion Prevention System (IPS). While a Security Information and Event Management (SIEM) system aggregates logs and can use correlation rules, it is the UEBA functionality that excels at this specific type of dynamic, behavioral anomaly detection. A Web Application Firewall (WAF) focuses on protecting web applications from attacks like SQL injection, not on user behavior baselining.
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ISC2 CISSP
Security Operations
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