Communication networks: Traffic data, network topologies, and routing anomalies

Abstract

Understanding modern data communication networks such as the Internet involves collection and analysis of data collected from deployed networks. It also calls for development of various tools for analysis of such datasets. Collected traffic data are used for characterization and modeling of network traffic, analysis of Internet topologies, and prediction of network anomalies. In this talk, I will describe collection and analysis of realtime traffic data using special purpose hardware and software tools. Analysis of such collected datasets indicates a complex underlying network infrastructure that carries traffic generated by a variety of the Internet applications. Data collected from the Internet routing tables are used to analyze Internet topologies and to illustrate the existence of historical trends in the development of the Internet. The Internet traffic data are also used to classify and detect network anomalies such as Internet worms, which affect performance of routing protocols and may greatly degrade network performance. Various statistical and machine learning techniques are used to classify test datasets, identify the correct traffic anomaly types, and design anomaly detection mechanisms.