1、Detect advanced threats and anomalous behavior using machine learning
User Behavior Analytics uses unsupervised machine learning algorithms to establish baseline behaviors of users, devices and applications, then searches for deviations to detect unknown and insider threats.
2、Enhance security visibility so you can act decisively
User Behavior Analytics visualizes threats across multiple phases of an attack to give security analysts a comprehensive understanding of attack root cause, scope, severity and timelines. This context-rich view enables analysts to rapidly assess impact, and make informed decisions quickly and confidently.
3、Simplify incident investigations to increase SOC efficiency
User Behavior Analytics automatically reduces billions of raw events down to tens of threats for rapid review, without the need for time-consuming human-fueled detective work performed by an army of highly skilled security and data science professionals.
