Novel EEG Sensor-Based Risk Framework for the Detection of Insider Threats in Safety Critical Industrial Infrastructure

Novel EEG Sensor-Based Risk Framework for the Detection of Insider Threats in Safety Critical Industrial Infrastructure

The loss or compromise of any safety critical industrial infrastructure can seriously impact the confidentiality, integrity, or delivery of essential services. Research has shown that such threats often come from malicious insiders. To identify these insiders, survey- and electrocardiogram-based app...

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Bibliographic Details
Main Authors: Ahmed Y. Al Hammadi, Dongkun Lee, Chan Yeob Yeun, Ernesto Damiani, Song-Kyoo Kim, Paul D. Yoo, Ho-Jin Choi
Format: Article
Language:English
Published: IEEE 2020-01-01
Series:IEEE Access
Subjects:
Deep learning
EEG sensors
fitness evaluation
insider threats
LSTM
safety critical industrial infrastructure
Online Access:https://ieeexplore.ieee.org/document/9258932/

Internet

https://ieeexplore.ieee.org/document/9258932/

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