Processing and Analytics of Big Network Traffic Data for Intrusion Detection

Abstract

Processing and analyzing a vast amount of data, in order to keep computer systems safe from attacks and intrusions, is a very time-consuming process. The solution for this problem is the development of distributed firewalls and antivirus programs that use machine-learning algorithms for data analytics and can perform security-related tasks in almost real-time. Developed distributed firewall that uses ML algorithms is presented. The proposed solution was implemented and tested over a big dataset in a short time period to measure its speed and accuracy.