Big Data Technologies for Security Event Correlation Based on Event Type Accounting
The work is devoted to the research of the approach to parallel data processing for performing the tasks of security events correlation based on big data technologies. Various methods and tasks of security events correlation, as well as technologies for processing big data, applicable for security monitoring tasks are considered. The main attention is paid to the tasks of identifying the links between security events types and the evaluation of the strength dependence of the events distribution in time. The implementation of the correlation tasks on the Spark platform is described, and the results of the experimental evaluation of the security events correlation processes are given.