A Fully Animated Interactive System for Clustering and Navigating Huge Graphs
GD '98 Proceedings of the 6th International Symposium on Graph Drawing
IPMatrix: An Effective Visualization Framework for Cyber Threat Monitoring
IV '05 Proceedings of the Ninth International Conference on Information Visualisation
A Multi-Faceted Approach towards Spam-Resistible Mail
PRDC '05 Proceedings of the 11th Pacific Rim International Symposium on Dependable Computing
A Novel Model for Detecting Application Layer DDoS Attacks
IMSCCS '06 Proceedings of the First International Multi-Symposiums on Computer and Computational Sciences - Volume 2 (IMSCCS'06) - Volume 02
Multi Layer Approach to Defend DDoS Attacks Caused by Spam
MUE '07 Proceedings of the 2007 International Conference on Multimedia and Ubiquitous Engineering
An Empirical Study of Spam and Spam Vulnerable email Accounts
FGCN '07 Proceedings of the Future Generation Communication and Networking - Volume 01
NetViewer: A Visualization Tool for Network Security Events
NSWCTC '09 Proceedings of the 2009 International Conference on Networks Security, Wireless Communications and Trusted Computing - Volume 01
The Case for Spam-Aware High Performance Mail Server Architecture
ICDCS '09 Proceedings of the 2009 29th IEEE International Conference on Distributed Computing Systems
The Performance of a Bare Machine Email Server
SBAC-PAD '09 Proceedings of the 2009 21st International Symposium on Computer Architecture and High Performance Computing
A dependability layer for large-scale distributed systems
International Journal of Grid and Utility Computing
A visualisation technique for network topology transformation within MonALISA monitoring framework
International Journal of Grid and Utility Computing
Visual Clustering of Spam Emails for DDoS Analysis
IV '11 Proceedings of the 2011 15th International Conference on Information Visualisation
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Spam email attacks are increasing at an alarming rate and have become more and more cunning in nature. This has necessitated the need for visual spam email analysis within an intrusion detection system to identify these attacks. The challenges are how to increase the accuracy of detection and how to visualise large volumes of spam email to better understand the analysis results and identify email attacks. This paper proposes a Density-Weight model that is to strengthen and extend the system capacity for analysis of network attacks in spam emails, including DDoS attacks. An interactive visual clustering method DA-TU is introduced to classify and display spam emails. The experimental results have shown that the proposed new model has improved the accuracy of intrusion detection and provides a better understanding of the nature of spam email attacks on though the network.