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One of the best ways to defend against both internal and external attacks is to use user and entity behavior analytics (UEBA) to continuously monitor user and device activity. UEBA learns about each user and creates a baseline of regular activities for each user and entity.
Any activity that deviates from this baseline gets flagged as an anomaly. The IT administrator can then investigate the issue and take the necessary steps to mitigate the risk. Powered by machine learning, UEBA solutions grow more effective the more experience they gain.
A risk score is calculated for each user and entity in the organization after comparing their actions to their baseline of regular activities. The risk score can range from anywhere between 0 to 100, indicating no risk to maximum risk, respectively. The risk score is dependent on factors such as the allotted weight of the action, the extent of the deviation from the baseline, the frequency of deviation, and the time elapsed since the deviation.
In addition to an overall risk score, each user and entity will also have an associated risk score for insider threats, account compromise, and data exfiltration. If the IT administrator feels an entity or user's risk score is too high, they can investigate it further and quickly stop any potential catastrophes.
Here are some activities that might increase the risk score of users and entities, indicating possible insider threats, account compromise, and data exfiltration.
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