Global-Local Attention-Based Butterfly Vision Transformer for Visualization-Based Malware Classification

Global-Local Attention-Based Butterfly Vision Transformer for Visualization-Based Malware Classification

In recent studies, convolutional neural networks (CNNs) are mostly used as dynamic techniques for visualization-based malware classification and detection. Though vision transformer (ViT) proved its efficiency in image classification, a few of the earlier studies developed a ViT-based malware classi...

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Bibliographic Details
Main Authors: Mohamad Mulham Belal, Divya Meena Sundaram
Format: Article
Language:English
Published: IEEE 2023-01-01
Series:IEEE Access
Subjects:
Vision transformer
global attention
local attention
malware classification
visualization-based malware classifier
parallel processing
Online Access:https://ieeexplore.ieee.org/document/10177144/

Internet

https://ieeexplore.ieee.org/document/10177144/

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