Toward a visualization-supported workflow for cyber alert management using threat models and human-centered design

Cyber network analysts follow complex processes in their investigations of potential threats to their network. Much research is dedicated to providing automated decision support in the effort to make their tasks more efficient, accurate, and timely. Support tools come in a variety of implementations from machine learning algorithms that monitor streams of data to visual analytic environments for exploring rich and noisy data sets. Cyber analysts, however, need tools which help them merge the data they already have and help them establish appropriate baselines against which to compare anomalies. Furthermore, existing threat models that cyber analysts regularly use to structure their investigation are not often leveraged in support tools. We report on our work with cyber analysts to understand the analytic process and how one such model, the MITRE ATT&CK Matrix [42], is used to structure their analytic thinking. We present our efforts to map specific data needed by analysts into this threat model to inform our visualization designs. We leverage this expert knowledge elicitation to identify a capability gaps that might be filled with visual analytic tools. We propose a prototype visual analytic-supported alert management workflow to aid cyber analysts working with threat models.