User behavior analytics
User Behavior Analytics ("UBA") as defined by Gartner, is a cybersecurity process about detection of insider threats, targeted attacks, and financial fraud. UBA solutions look at patterns of human behavior, and then apply algorithms and statistical analysis to detect meaningful anomalies from those patterns - anomalies that indicate potential threats.'[1][2] Instead of tracking devices or security events, UBA tracks a system's users.[3]
The problem UBA responds to, as described by Nemertes Research CEO Johna Till Johnson, is that "Security systems provide so much information that it's tough to uncover information that truly indicates a potential for real attack. Analytics tools help make sense of the vast amount of data that SIEM, IDS/IPS, system logs, and other tools gather. UBA tools use a specialized type of security analytics that focuses on the behavior of systems and the people using them. UBA technology first evolved in the field of marketing, to help companies understand and predict consumer-buying patterns. But as it turns out, UBA can be extraordinarily useful in the security context too." [4]