Jennifer Cowley’s scientific contributions

The human visual system is generally more adept at inferring meaning from graphical objects and natural scene elements than reading alphanumeric characters. Graphical objects like charts and graphs in cybersecurity dashboards often lack the requisite numbers of features to depict behaviors of complex network data. For example, bar charts afford few features to encode a panoply of parameters in network data. Furthermore, dashboard visualizations seldom support the transition of human work from situation awareness building to requisite responses during intrusion detection events. This research effort aims to identify how graphical objects (also referred as data-shapes) depicted in Virtual Reality tools, developed in accordance with an analyst’s mental model of an intrusion detection event, can enhance analyst’s situation awareness. We demonstrate the proposed approach using Locked Shields 16 CDX network traffic. Implications of this study and future case study are discussed.