An intelligent, interactive tool for exploration and visualization of time-oriented security data
Proceedings of the 3rd international workshop on Visualization for computer security
Proceedings of the 3rd international workshop on Visualization for computer security
Interactively combining 2D and 3D visualization for network traffic monitoring
Proceedings of the 3rd international workshop on Visualization for computer security
A Component-Based Framework for Visualization of Intrusion Detection Events
Information Security Journal: A Global Perspective
Toward a Scalable Visualization System for Network Traffic Monitoring
IEICE - Transactions on Information and Systems
An intelligent contextual support system for intrusion detection tasks
Proceedings of the Symposium on Computer Human Interaction for the Management of Information Technology
Neural visualization of network traffic data for intrusion detection
Applied Soft Computing
RT-MOVICAB-IDS: Addressing real-time intrusion detection
Future Generation Computer Systems
Visualizing PHPIDS log files for better understanding of web server attacks
Proceedings of the Tenth Workshop on Visualization for Cyber Security
NAVSEC: a recommender system for 3D network security visualizations
Proceedings of the Tenth Workshop on Visualization for Cyber Security
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Intrusion detection systems have been popular tools in the battle against adversaries who, for whatever reason, desire to break into networks, compromise hosts, and steal valuable information. One problem with current implementations, however, is the sheer number of alerts they can generate, many of which tend to be false alarms. This drawback makes effective use of such systems a challenging task. In this paper we explore three-dimensional approaches to visualizing network intrusion detection system alerts and aggregated network statistics in order to provide the system administrator with a better picture of the events occurring on his or her network. While some research has been done using twodimensional concepts, 3D approaches have not received much attention with regard to detecting network intrusions. Evaluation of our visualizations using the 1999 DARPA Intrusion Detection Evaluation data set demonstrates the potential benefit of utilizing the third dimension. We show how a number of attack types in the data set generate visual evidence of abnormal activity that a security administrator might use as motivation for further investigation.