GCSA-ResNet: a deep neural network architecture for Malware detection

GCSA-ResNet: a deep neural network architecture for Malware detection

Abstract With the exponential growth in the quantity and complexity of malware, traditional detection methods face severe challenges. This paper proposes GCSA-ResNet, a novel deep learning model that significantly enhances malware detection performance by integrating the Global Channel-Spatial Atten...

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Bibliographic Details
Main Authors: Yukang Fan, Kun Zhang, Bing Zheng, Yu Zhou, Jinyang Zhou, Wenting Pan
Format: Article
Language:English
Published: Nature Portfolio 2025-07-01
Series:Scientific Reports
Subjects:
Malware visualization
Malware detection
Deep learning
Attention mechanism
Feature fusion
Online Access:https://doi.org/10.1038/s41598-025-10561-6
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https://doi.org/10.1038/s41598-025-10561-6

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