Abstract
The importance of the Internet and our dependency on computer networks are steadily growing, which results in high costs and substantial consequences in case of successful intrusions, stolen data, and interrupted services. At the same time, a trend towards massive attacks against the network infrastructure is noticeable. Therefore, monitoring large networks has become an important field in practice and research. Through monitoring systems, attacks can be detected and analyzed to gain knowledge of how to better protect the network in the future. In the scope of this paper, we present a system to analyze NetFlow data using a relational database system. NetFlow records are linked with alerts from an intrusion detection system to enable efficient exploration of suspicious activity within the monitored network. Within the system, the monitored network is mapped to a TreeMap visualization, the attackers are arranged at the borders and linked using splines parameterized with prefix information. In a series of case studies, we demonstrate how the tool can be used to judge the relevance of alerts, to reveal massive distributed attacks, and to analyze service usage within a network.
BibTeX (Download)
@inproceedings{Fischer2008Large-scale,
title = {Large-scale Network Monitoring for Visual Analysis of Attacks},
author = {Fabian Fischer and Florian Mansmann and Daniel A. Keim and Stephan Pietzko and Marcel Waldvogel},
url = {https://netfuture.ch/wp-content/uploads/2008/fischer08large-scale.pdf},
year = {2008},
date = {2008-08-15},
urldate = {1000-01-01},
booktitle = {5th International Workshop on Visualization for Cyber Security (VizSEC 2008)},
address = {Cambridge, MA, USA},
abstract = {The importance of the Internet and our dependency on computer networks are steadily growing, which results in high costs and substantial consequences in case of successful intrusions, stolen data, and interrupted services. At the same time, a trend towards massive attacks against the network infrastructure is noticeable. Therefore, monitoring large networks has become an important field in practice and research. Through monitoring systems, attacks can be detected and analyzed to gain knowledge of how to better protect the network in the future. In the scope of this paper, we present a system to analyze NetFlow data using a relational database system. NetFlow records are linked with alerts from an intrusion detection system to enable efficient exploration of suspicious activity within the monitored network. Within the system, the monitored network is mapped to a TreeMap visualization, the attackers are arranged at the borders and linked using splines parameterized with prefix information. In a series of case studies, we demonstrate how the tool can be used to judge the relevance of alerts, to reveal massive distributed attacks, and to analyze service usage within a network.},
keywords = {Intrusion Detection, Security},
pubstate = {published},
tppubtype = {inproceedings}
}
