Graph-Based P2P Traffic Classification at the Internet Backbone
Marios Iliofotou, Hyun-chul Kim, Michalis Faloutsos, Michael Mitzenmacher, Prashanth Pappu, George Varghese · 2009
Monitoring network traffic and classifying applications are essential functions for network administrators. In this paper, we consider the use of traffic dispersion graphs (TDGs) to classify network traffic. Given a set of flows, a TDG is a graph with an edge between any two IP addresses that communicate; thus TDGs capture network-wide interactions. Using TDGs, we develop an application classification framework dubbed Graption (Graph-based classification). Our framework provides a systematic way to harness the power of network-wide behavior, flow-level characteristics, and data mining techniques. As a proof of concept, we instantiate our framework to detect P2P applications, and show that it can identify P2P traffic with recall and precision greater than 90% in backbone traces, which are particularly challenging for other methods.