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User and entity behavior analytics (UEBA) software uses artificial intelligence (AI) and machine learning (ML) to analyze the actions that users and devices take on a network to identify threats. Humans are creatures of habit, and deviation from their normal behaviors — especially when it comes to technology — may signify a lost or stolen device. For example, if a user typically downloads files directly to their device, but then one day plugs in a USB drive to download a file, that may indicate a bad actor has accessed the network from the authorized user’s device.
In addition, UEBA analyzes and monitors devices for potentially malicious activity. A server that receives a spike in access requests may indicate a distributed denial-of-service (DDoS) attack, or a cloud application attempting to access a different part of the network than usual may indicate a breach in that application. Depending on how an organization has set up its UEBA software, the system may either simply alert the IT team of the threat or block access until IT has investigated the activity.
UEBA takes some time to implement because the AI has to establish a baseline for behavior. Plus, it’s mostly a monitoring tool used to detect threats with limited remediation features in most cases. Therefore, organizations must pair UEBA with other cybersecurity software, like network-securing firewalls or threat-responsive XDR. Because of this, companies can either purchase UEBA software as a standalone solution or as part of a larger cybersecurity suite.
The key to a successful UEBA implementation is integrating the system with as many other devices and applications as possible within an organization. This will give it the widest reach, allowing it to gather more data and give IT context for potential threats that they need to investigate. That way, IT has the information they need to evaluate a breach quickly and remediate it before the threat can cause too much damage.
Explore the Best User and Entity Behavior Analytics (UEBA) Tools on eSecurity Planet.