Detecting anomalous user behavior using generative models of user actions

摘要

A method for detecting abnormal behavior of users is disclosed. Processors identify from a log of user activity, a first number of actions performed by a user over a first time period that match a pattern of user activity for a task associated with one or more roles of the users. Processors also identify from the log of user activity, a second number of actions performed by the user over a second time period that match the pattern of user activity. Processors calculate an amount of deviation between the first number of actions and the second number of actions. The deviation identifies a difference between amounts of time spent in the one or more roles. Processors then determine whether the amount of deviation between the first number of actions and the second number of actions exceeds a threshold for abnormal behavior.