Unmasking insider threats using a robust hybrid optimized generative pretrained neural network approach

Unmasking insider threats using a robust hybrid optimized generative pretrained neural network approach

Abstract The design of insider threat detection models utilizing neural networks significantly improve its performance and ensures the precise identification of security breaches within network infrastructure. However, developing insider threat detection models involves substantial challenges in add...

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Bibliographic Details
Main Authors: P. Lavanya, H. Anila Glory, Manuj Aggarwal, V. S. Shankar Sriram
Format: Article
Language:English
Published: Nature Portfolio 2025-07-01
Series:Scientific Reports
Subjects:
Generated adversaries
Chebyshev solvers
Pretrained model
Regularization
Hyperparameter optimization
Insider threat detection
Online Access:https://doi.org/10.1038/s41598-025-12127-y
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https://doi.org/10.1038/s41598-025-12127-y

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