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Navigating Cyberthreat Intelligence with CYBEX-P: Dashboard Design and User Experience
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As the world’s data exponentially grows, two major problems increasingly need to be solved. The first is how to interpret large and complex datasets so that actionable insight can be achieved. The second is how to effectively protect these data and the assets they represent. This thesis’ topic lies at the intersection of these two crucial issues. The research presented in the thesis learns from past work on applying data visualization to multiple domains, with a focus on cybersecurity visualization. These learnings were then applied to a new research area: cybersecurity information sharing. The frontend considerations for CYBEX-P, a cybersecurity information sharing platform developed at UNR, are discussed in detail. A user-facing web application was developed from these requirements, resulting in an approachable, highly visual cyberthreat investigation tool. The threat-intelligence graph at the center of this dashboard-style tool allows analysts to interact with indicators of compromise and efficiently reach security conclusions. In addition to research and related software development, a user study was conducted with participants from cybersecurity backgrounds to test different visualization configurations. Subsequent analysis revealed that the misuse of simple visual properties can lead to perilous reductions in accuracy and response-time. Recommendations are provided for avoiding these pitfalls and balancing information density. The study results inform the final functionalities of the CYBEX-P front end and serve as a foundation for similar prospective tools. By improving how insights can be extracted from large cybersecurity datasets, the work presented in the thesis paves the way towards a more secure and informed future in a technology-driven world.