User and Entity Behavior Analytics (UEBA)
User and Entity Behavior Analytics (UEBA) is a category of security solutions that use innovative analytics technology, including machine learning and deep learning, to discover abnormal and risky behavior by users, machines, and other entities on the corporate network in conjunction with a SIEM.
Namely, SIEM is oriented on point-in-time analysis of known threats. UEBA, meanwhile, provides real-time analysis of activity that can detect unknown threats as they happen and even predict a security incident based on anomalous behavior by a user or entity.
How UEBA Works?
As a native security analytics module in the UEBA platform, UEBA utilizes machine learning to identify normal behavior and alert to risky deviations that suggest insider threats, lateral movement, or attacks at the end of the cyber kill chain.
Detect compromised accounts and privilege abuse through user behavior analysis.
Meet data compliance standards including PCI and HIPAA.
Detect late-stage attacks by identifying when data is being exfiltrated from your environment.
Monitor all your connected devices and networks, from industrial control systems to the cloud. Detect abnormal configurations or alterations to security logging to prevent covert attacker access.
Identify compromised credentials and passwords by observing logins that are indicative of account abuse by attackers.
Use models of login times and locations as well as login hostnames to establish common login behavior for users within a network.
See when devices are connecting to unusual addresses and sending data outside of their normal boundaries.
Alert to abnormal data flow volumes and destinations with combined machine learning and statistical anomaly detection.
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