Graph Based Statistical Analysis of Network Traffic

We propose a method for analyzing traffic data in large computer networks such as big enterprise networks or the Internet. Our approach combines graph theoretical representation of the data and graph analysis with novel statistical methods for discovering pattern and time-related anomalies. We model the traffic as a graph and use temporal characteristics of the data in order to decompose it into subgraphs corresponding to individual sessions, whose characteristics are then analyzed using statistical methods. The goal of that analysis is to discover patterns in the network traffic data that might indicate intrusion activity or other malicious behavior.