DTITD: An Intelligent Insider Threat Detection Framework Based on Digital Twin and Self-Attention Based Deep Learning Models

DTITD: An Intelligent Insider Threat Detection Framework Based on Digital Twin and Self-Attention Based Deep Learning Models

Recent statistics and studies show that the loss generated by insider threats is much higher than that generated by external attacks. More and more organizations are investing in or purchasing insider threat detection systems to prevent insider risks. However, the accurate and timely detection of in...

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Bibliographic Details
Main Authors: Zhi Qiang Wang, Abdulmotaleb El Saddik
Format: Article
Language:English
Published: IEEE 2023-01-01
Series:IEEE Access
Subjects:
Digital twin
cybersecurity
insider threat
deep learning
transformer
BERT
Online Access:https://ieeexplore.ieee.org/document/10285086/

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