An Investigation of Insider Threat Mitigation Based on EEG Signal Classification

An Investigation of Insider Threat Mitigation Based on EEG Signal Classification

This study proposes a scheme to identify insider threats in nuclear facilities through the detection of malicious intentions of potential insiders using subject-wise classification. Based on electroencephalography (EEG) signals, a classification model was developed to identify whether a subject has...

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Bibliographic Details
Main Authors: Jung Hwan Kim, Chul Min Kim, Man-Sung Yim
Format: Article
Language:English
Published: MDPI AG 2020-11-01
Series:Sensors
Subjects:
nuclear security
insider threat
electroencephalography
machine learning
implicit intention
subject-wise classification
Online Access:https://www.mdpi.com/1424-8220/20/21/6365

Internet

https://www.mdpi.com/1424-8220/20/21/6365

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