Organizations Data Integrity Providing through Employee Behavioral Analysis Algorithms

This article discusses the development of mathematical support and software for detecting anomalous behavior of users based on biometric characteristics of their behavior analysis. One of the challenges in intelligent UBA (User Behavior Analytics) systems is acquisition of useful information from a large volumes of unstructured, unmatched data. Methods and algorithms of intelligent data processing and machine learning used in UBA/DSS systems help to work on a task of solving problems of data analysis of different directivities. It is proposed an application of machine learning methods in implementation of mobile UBA system. There was formed the list of the most significant factors submitted to the input of the analyzing methods during the study. Two approaches of detecting abnormal user behavior have been proposed. The application of machine learning techniques in intelligent UBA systems will make it possible to predict information risks and insider excfiltration of these organizations in advance.