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9 April 2007Analysis and visualization of large complex attack graphs for networks security
Hongda Chen,1 Genshe Chen,2 Erik Blasch,3 Martin Kruger,4 Irma Sityar5
1Intelligent Automation, Inc. (United States) 2Intelligent Automation Inc. (United States) 3Air Force Research Lab. (United States) 4Office of Naval Research (United States) 5Alion Science and Technology (United States)
In this paper, we have proposed a comprehensive and innovative approach for analysis and visualization of large
complex multi-step cyber attack graphs. As an automated tool for cyber attack detection, prediction, and visualization,
the newly proposed method transforms large quantities of network security data into real-time actionable intelligence,
which can be used to (1) provide guidance on network hardening to prevent attacks, (2) perform real-time attack event
correlation during active attacks, and (3) formulate post-attack responses. We show that it is possible to visualize the
complex graphs, including all possible network attack paths while still keeping complexity manageable. The proposed
analysis and visualization tool provides an efficient and effective solution for predicting potential attacks upon observed
intrusion evidence, as well as interactive multi-resolution views such that an analyst can first obtain high-level overviews
quickly, and then drill down to specific details.
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Hongda Chen, Genshe Chen, Erik Blasch, Martin Kruger, Irma Sityar, "Analysis and visualization of large complex attack graphs for networks security," Proc. SPIE 6570, Data Mining, Intrusion Detection, Information Assurance, and Data Networks Security 2007, 657004 (9 April 2007); https://doi.org/10.1117/12.720035