A Lightweight Model for Malicious Code Classification Based on Structural Reparameterisation and Large Convolutional Kernels

A Lightweight Model for Malicious Code Classification Based on Structural Reparameterisation and Large Convolutional Kernels

Abstract With the advancement of adversarial techniques for malicious code, malevolent attackers have propagated numerous malicious code variants through shell coding and code obfuscation. Addressing the current issues of insufficient accuracy and efficiency in malicious code classification methods...

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Bibliographic Details
Main Authors: Sicong Li, Jian Wang, Yafei Song, Shuo Wang, Yanan Wang
Format: Article
Language:English
Published: Springer 2024-02-01
Series:International Journal of Computational Intelligence Systems
Subjects:
Malware variant detection
Convolutional neural network
Structurral reparameterisation
Large kernel convolution
Image size normalisation
Online Access:https://doi.org/10.1007/s44196-023-00400-9

Internet

https://doi.org/10.1007/s44196-023-00400-9

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