Which of the following is the PRIMARY indicator used in User Entity and Behavior Analytics (UEBA) to detect anomalies in user behavior?
Correct answer
1.Most frequently accessed data
First login time
Highest number of failed login attempts
Most recent login time
The correct answer: Most frequently accessed data: UEBA (User and Entity Behavior Analytics) is a cybersecurity process that takes note of the normal conduct of users and then detects any anomalous behavior or instances when they deviate from these patterns. The “most frequently accessed data” is a key indicator used by UEBA.
The reason is that changes in the data a user regularly accesses can indicate potentially harmful actions. For instance, if a user who typically accesses a particular set of data suddenly starts accessing a different, more sensitive set of data, it could signify a compromised account or insider threat. UEBA systems detect such sudden changes in behavior and alert cybersecurity teams accordingly.
The incorrect answers: The first login time isn’t a primary indicator used in UEBA. This is because it usually remains constant for a given user.
It may be used as a secondary factor in the context of user behavior, such as tracking when a new user starts exhibiting unusual behavior, but it’s not the primary means of identifying anomalous actions. The highest number of failed login attempts could indicate a brute force attack or account compromise attempt, but it isn’t a primary indicator used in UEBA.
Failed logins fall under the umbrella of traditional security tools and are usually monitored by intrusion detection systems (IDS) or security information and event management (SIEM) solutions. While it’s true that UEBA might consider failed logins in its broader behavioral analysis, it’s not the main method UEBA uses to identify abnormal behavior.
Most recent login time is an important piece of information for various security practices, and can be used as a secondary indicator in UEBA, but it isn’t the primary indicator of abnormal behavior. The primary focus of UEBA is to understand consistent patterns in data access and other activities over time, not isolated incidents like a single login event. A sudden change in login time might be taken into account, but it’s the repetitive anomalies in behavior that UEBA systems chiefly look out for.
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