Exploiting dynamicity in graph-based traffic analysis

Abstract

Network traffic can be represented by a Traffic Dispersion Graph (TDG) that contains an edge between two nodes that send a particular type of traffic (e.g., DNS) to one another. TDGs have recently been proposed as an alternative way to interpret and visualize network traffic. Previous studies have focused on static properties of TDGs using graph snapshots in isolation. In this work, we represent network traffic with a series of related graph instances that change over time. This representation facilitates the analysis of the dynamic nature of network traffic, providing additional descriptive power. For example, DNS and P2P graph instances can appear similar when compared in isolation, but the way the DNS and P2P TDGs change over time differs significantly. To quantify the changes over time, we introduce a series of novel metrics that capture changes both in the graph structure (e.g., the average degree) and the participants (i.e., IP addresses) of a TDG. We apply our new methodologies to improve graph-based traffic classification and to detect changes in the profile of legacy applications (e.g., e-mail).