Fig 2 - uploaded by Kaur Kullman
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Head-Up Display showing labels of visualized groups that the user focuses on, retaining visual connetions to those with Bézier curves. HUD is used also for other interaction and feedback purposes.
Source publication
Cybersecurity practitioners face the challenge of monitoring complex and large datasets. These could be visualized as time-varying node-link graphs, but would still have complex topologies and very high rates of change in the attributes of their links (representing network activity). It is natural, then, that the needs of the cybersecurity domain h...
Contexts in source publication
Context 1
... information is displayed on a head-up display (HUD) that is perceived to be positioned a few meters away from the user in MR and about 30m in VR. The HUD smoothly follows the direction of user's head in order to remain in the user's field of view (see Fig. 2). This virtual distance was chosen to allow a clear distinction between the HUD and the network itself, which is stereoscopically apparent as being nearer to the ...
Context 2
... selected, detailed information about the selected object (node or edge) is shown on a line of text rendered next to user's hand, (Shneiderman Task Level 4). 2. grab (or pinch) nodes and move (or throw) these around to better perceive its relations by observing the edges that are originating or terminating in that node: humans perceive the terminal locations of moving lines better than that of static ones, (Shneiderman Task Levels 3, 5). In addition to active gestures and hand recognition, the user's position and gaze (instead of just their head direction) are used if available to decide which visualization sub-groups to focus on, to enable textual labels, to hide enclosures, to enable update routines, colliders, etc. (Shneiderman Task Levels 2, 3, 4, 5, 7). Therefore, depending on user's direction and location amongst the visualization Fig. 3. ...
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Citations
... As XR has been shown to enable domain scientists in other fields to develop a better underestanding of their data [7], we seek to use XR to support GEOS users. Our implementation is in NASA's open source toolkit for XR, the Mixed Reality Exploration Toolkit (MRET) [8], because MRET has a track record in supporting the modular development of tailored visualizations for other application domains [9]. ...
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... The first image in the panel depicts an overview of the network layout used in the present study. The second image is a representative close-up (taken fromKullman & Engel, 2022). (C) Images depicting the 2D network topology as shown in the Arkime condition. ...
Background
Cyber defense decision-making during cyber threat situations is based on human-to-human communication aiming to establish a shared cyber situational awareness. Previous studies suggested that communication inefficiencies were among the biggest problems facing security operation center teams. There is a need for tools that allow for more efficient communication of cyber threat information between individuals both in education and during cyber threat situations.
Methods
In the present study, we compared how the visual representation of network topology and traffic in 3D mixed reality vs. 2D affected team performance in a sample of cyber cadets ( N = 22) cooperating in dyads. Performance outcomes included network topology recognition, cyber situational awareness, confidence in judgements, experienced communication demands, observed verbal communication, and forced choice decision-making. The study utilized network data from the NATO CCDCOE 2022 Locked Shields cyber defense exercise.
Results
We found that participants using the 3D mixed reality visualization had better cyber situational awareness than participants in the 2D group. The 3D mixed reality group was generally more confident in their judgments except when performing worse than the 2D group on the topology recognition task (which favored the 2D condition). Participants in the 3D mixed reality group experienced less communication demands, and performed more verbal communication aimed at establishing a shared mental model and less communications discussing task resolution. Better communication was associated with better cyber situational awareness. There were no differences in decision-making between the groups. This could be due to cohort effects such as formal training or the modest sample size.
Conclusion
This is the first study comparing the effect of 3D mixed reality and 2D visualizations of network topology on dyadic cyber team communication and cyber situational awareness. Using 3D mixed reality visualizations resulted in better cyber situational awareness and team communication. The experiment should be repeated in a larger and more diverse sample to determine its potential effect on decision-making.
... The first image in the panel depicts an overview of the network layout used in the present study. The second image is a representative close-up (taken fromKullman & Engel, 2022). (C) Images depicting the 2D network topology as shown in the Arkime condition. ...
Cyber defense decision-making during cyber threat situations is based on human-to-human communication aiming to establish a shared cyber situational awareness. Previous studies suggested that communication inefficiencies were among the biggest problems facing security operation center teams. There is a need for tools that allow for more efficient communication of cyber threat information between individuals both in education and during cyber threat situations. In the present study, we compared how the visual representation of network topology and traffic in 3D mixed reality versus 2D affected team performance in a sample of cyber cadets (N = 22) cooperating in dyads. Performance outcomes included network topology recognition, cyber situational awareness, confidence in judgements, experienced communication demands, observed verbal communication, and forced choice decision-making. The study utilized network data from the NATO CCDCOE 2022 Locked Shields cyber defense exercise. We found that participants using the 3D mixed reality visualization had better cyber situational awareness than participants in the 2D group. The most apparent difference was in the detection of the top five Red Team hosts targeting Blue Team systems, where the traffic associated with the identified Red Team hosts differed in the tens of thousands between the groups. The 3D mixed reality group was generally more confident in their judgments except when performing worse than the 2D group on the topology recognition task (which favored the 2D condition). Participants in the 3D mixed reality group experienced less communication demands, and performed more verbal communication aimed at establishing a shared mental model and less communications discussing task resolution. There were no differences in decision-making between the groups. This could be due to cohort effects such as formal training or the modest sample size. This is the first study comparing the effect of 3D mixed reality and 2D visualizations of network topology on dyadic cyber team communication and cyber situational awareness. Using 3D mixed reality visualizations resulted in better cyber situational awareness and team communication. The experiment should be repeated in a larger and more diverse sample to determine its potential effect on decision-making.
