Project: FocalPoint: Adaptive Level of Detail for Network Maps and Attack Graphs

Partner: Uncharted Software Inc.
Dates: 2015 - Present
Participants: Jamieson, G., Carrasco, C. , Kortschot, Sean
Description: In recent years, cyber attacks against network systems have become increasingly prominent. Network maps and attack graphs are visualizations used to identify and correct system weaknesses that may lead to these attacks. Currently, these visualizations are too complex to support appropriate user performance in perception, comprehension, and projection of the cyber battlespace situation. In order to improve situation awareness under these conditions, we will join Uncharted Software Inc. in developing an adaptive system for determining appropriate level of detail (LOD) views for network systems and attack graphs. This adaptive system will involve measurement of both the user’s and the system’s current state in order to determine appropriate levels of information aggregation in a real-time, context-specific manner. While this research project will have direct applications in the cyber domain, the technical approach and methods developed will also be broadly applicable to other forms of adaptive visualizations.
Publications:

View PDF Soh, H., Sanner, S., White, M., & Jamieson, G. (2017, March). Deep Sequential Recommendation for Personalized Adaptive User Interfaces. In Proceedings of the 22nd International Conference on Intelligent User Interfaces (pp. 589-593). ACM.

View PDF Inibhunu, C., Langevin, S., Ralph, S., Kronefeld, N., Soh, H., Jamieson, G., Sanner, S., Kortschot, S. W., Carrasco, C. & White, M., "Adapting Level of Detail in User Interfaces for Cybersecurity Operations", Resilience Week (RWS), TBD, 2016.

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