Feasibility of Applying a Human Bio-signals Monitoring to Minimize Insider Threats
With the on-going global war on terror, a potential terrorist attack on a Nuclear Power Plant (NPP) is getting a lot of attention. In particular, the potential threat of an insider is a major concern as it could lead to the loss of a nationally critical asset and thus deserves serious consideration. The current approach to preventing an insider threat is the Insider Mitigation Program (IMP) based on periodic self-assessment or peer and manager review of specific employees. These are potentially biased and subjective assessments and are unreliable. Also, as the approach is reactive-based, identifying a problem employee could be too late to protect NPP assets (i.e., confidential information and nuclear materials). Thus, a new approach for detecting and predicting an insider is necessary. We propose a proactive approach based on using bio-signals as an alternative. To address the vulnerability of current insider detection systems, our studies investigated the possibility of insider detection and prediction by using biosignals (electroencephalogram (EEG), electrocardiogram (ECG), and galvanic skin response (GSR)). But one main question remained in the previous studies was: Is the method using key EEG indicators specific enough to discern the difference between a normal worker's motivation level change and being ready to commit a crime? This study examined the answer to the question.