Interactive Exploration of Data Traffic with Hierarchical Network Maps

Abstract

Network communication has become indispensable in business, education, and government. With the pervasive role of the Internet as a means of sharing information across networks, its misuse for destructive purposes, such as spreading malicious code, compromising remote hosts or damaging data through unauthorized access, has grown immensely in the recent years. The classical way of monitoring the operation of large network systems is by analyzing the system logs for detecting anomalies. In this work, we introduce Hierarchical Network Map, an interactive visualization technique for gaining a deeper insight into network flow behavior by means of user-driven visual exploration. Our approach is meant as an enhancement to conventional analysis methods based on statistics or machine learning. We use multidimensional modeling combined with position and display awareness to view source and target data of the hosts in a hierarchical fashion with the ability to interactively change the level of aggregation or apply filtering. The interdisciplinary approach integrating data warehouse technology, information visualization, and decision support, brings about the benefit of efficiently collecting the input data and aggregating over very large data sets, visualizing the results, and providing interactivity to facilitate analytical reasoning.