Abstract
The mission of a Cyber Security Officer (CSO) during a cyberattack is to identify anomalies in visual signals and to ascertain whether they are hostile. These signals occur in an environment overflowing with data, which is constantly shifting shape and density, and in which the rate of change keeps accelerating and novel anomalies arise. In this environment, previous experience is disadvantageous and oftentimes harms the ability of a CSO to identify novel patterns of anomalies. This study tested, in a moderated mediation model, the effect of Immersive Virtual Reality (IVR), while identifying hidden forms in Embedded Figure Tasks (EFTs), on the ability to detect a novel and unknown anomaly. Through a quasi-experiment with repeated measurements, we compared five research groups, four of which practiced cognitive intervention while detecting cyber anomalies. The improvement was tested through a pre-test and post-test procedure. A cluster sampling involved 120 students recruited from the Academy of Computer and Cyber Training at the Telecommunication Branch of the Israel Defense Forces. We found that participants who practiced the EFTs in an IVR informationdiluted environment (VRLVL) detected novel anomalies faster than the control group. We also found that the higher the thought elasticity of the participants in an IVR highly-loaded environment (VRHVL), the higher their speed in detecting novel anomalies.
Author Information
David Passig, Bar-Ilan University, Israel
Reut Hochman, Bar-Ilan University, Israel
Paper Information
Conference: IICE2022
Stream: Professional Training
This paper is part of the IICE2022 Conference Proceedings (View)
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To cite this article:
Passig D., & Hochman R. (2022) Enhancing the Efficacy of Identifying Visual Patterns and Novel Anomalies of Cyber-Defenders With 3D Immersive VR ISSN: 2189-1036 – The IAFOR International Conference on Education – Hawaii 2022 Official Conference Proceedings https://doi.org/10.22492/issn.2189-1036.2022.6
To link to this article: https://doi.org/10.22492/issn.2189-1036.2022.6
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