Eye Tracking Metrics for Insider Threat Detection in a Simulated Work Environment
| Autor: | Ryan W. Wohleber, Gerald Matthews, Eric Ortiz, Lauren Reinerman-Jones |
|---|---|
| Rok vydání: | 2017 |
| Předmět: |
Computer science
05 social sciences Insider threat Computer security computer.software_genre 050105 experimental psychology Work environment Insider Medical Terminology 03 medical and health sciences 0302 clinical medicine Eye tracking 0501 psychology and cognitive sciences computer 030217 neurology & neurosurgery Medical Assisting and Transcription |
| Zdroj: | Proceedings of the Human Factors and Ergonomics Society Annual Meeting. 61:202-206 |
| ISSN: | 1071-1813 2169-5067 |
| Popis: | Insider Threats (ITs) are hard to identify because of their knowledge of the organization and motivation to avoid detection. One approach to detecting ITs utilizes Active Indicators (AI), stimuli that elicit a characteristic response from the insider. The present research implemented this approach within a simulation of financial investigative work. A sequence of AIs associated with accessing a locked file was introduced into an ongoing workflow. Participants allocated to an insider role accessed the file illicitly. Eye tracking metrics were used to differentiate insiders and control participants performing legitimate role. Data suggested that ITs may show responses suggestive of strategic concealment of interest and emotional stress. Such findings may provide the basis for a cognitive engineering approach to IT detection. |
| Databáze: | OpenAIRE |
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