Intrusion detection analysis requires understanding the context of an event, usually discovered by examining packet-level detail. When analysts attempt to construct the big picture of a security event, they must move between high-level representations and these low-level details. This continual shifting places a substantial cognitive burden on the analyst, who must mentally store and transfer information between these levels of analysis. This article presents an information visualization tool, the time-based network traffic visualizer (TNV), which reduces this burden. TNV augments the available support for discovering and analyzing anomalous or malicious network activity. The system is grounded in an understanding of the work practices of intrusion detection analysts, particularly foregrounding the overarching importance in the analysis task of integrating contextual information into an understanding of the event under investigation. TNV provides low-level, textual data and multiple, linked visualizations that enable analysts to simultaneously examine packet-level detail within the larger context of activity.
ASJC Scopus subject areas
- Computer Graphics and Computer-Aided Design