The purpose of this paper is to investigate a feasibility of detecting and predicting a worker having malicious intention based on Electroencephalogram (EEG). The malicious intended worker, so called an insider threat, is global Cyber security concern in nuclear industries as well as private sectors. The current approach to preventing the human threat is based on administrative and qualitative measures such as peer and manager reviews. These measures are subjective and biased assessment. Thus, quantitative and technical approach is necessary. Our previous study reported the possibility of insider threat detection using EEG indicators based on scenario based
tasks. This study validated the results from our previous study results using new experiment design. The design is mimicking a potentially intentional action from an insider. This action is related to view highly secured files or steal high-level information. Results of EEG indicators have a similar tendency with previous scenario-based tasks. The resulting from new tasks could be utilized for the identification of potential insider.

Published in: Internet Technology and Secured Transactions (ICITST-2018)

• Date of Conference: 10-13 December 2018
• DOI: 10.2053/ICITST.WorldCIS.WCST.WCICSS.2018.0027
• ISBN: 978-1-908320-94-0
• Conference Location: University of Cambridge, Churchill College