Share Email Print
cover

Proceedings Paper

Visualization techniques for computer network defense
Author(s): Justin M. Beaver; Chad A. Steed; Robert M. Patton; Xiaohui Cui; Matthew Schultz
Format Member Price Non-Member Price
PDF $14.40 $18.00

Paper Abstract

Effective visual analysis of computer network defense (CND) information is challenging due to the volume and complexity of both the raw and analyzed network data. A typical CND is comprised of multiple niche intrusion detection tools, each of which performs network data analysis and produces a unique alerting output. The state-of-the-practice in the situational awareness of CND data is the prevalent use of custom-developed scripts by Information Technology (IT) professionals to retrieve, organize, and understand potential threat events. We propose a new visual analytics framework, called the Oak Ridge Cyber Analytics (ORCA) system, for CND data that allows an operator to interact with all detection tool outputs simultaneously. Aggregated alert events are presented in multiple coordinated views with timeline, cluster, and swarm model analysis displays. These displays are complemented with both supervised and semi-supervised machine learning classifiers. The intent of the visual analytics framework is to improve CND situational awareness, to enable an analyst to quickly navigate and analyze thousands of detected events, and to combine sophisticated data analysis techniques with interactive visualization such that patterns of anomalous activities may be more easily identified and investigated.

Paper Details

Date Published: 2 June 2011
PDF: 9 pages
Proc. SPIE 8019, Sensors, and Command, Control, Communications, and Intelligence (C3I) Technologies for Homeland Security and Homeland Defense X, 801906 (2 June 2011); doi: 10.1117/12.883487
Show Author Affiliations
Justin M. Beaver, Oak Ridge National Lab. (United States)
Chad A. Steed, Oak Ridge National Lab. (United States)
Robert M. Patton, Oak Ridge National Lab. (United States)
Xiaohui Cui, Oak Ridge National Lab. (United States)
Matthew Schultz, Liberty Univ. (United States)


Published in SPIE Proceedings Vol. 8019:
Sensors, and Command, Control, Communications, and Intelligence (C3I) Technologies for Homeland Security and Homeland Defense X
Edward M. Carapezza, Editor(s)

© SPIE. Terms of Use
Back to Top