Search research articles

ABOUT JoVE

Overview Leadership Blog JoVE Help Center

AUTHORS

Publishing Process Editorial Board Scope & Policies Peer Review FAQ Submit

LIBRARIANS

Testimonials Subscriptions Access Resources Library Advisory Board FAQ

RESEARCH

JoVE Journal Methods Collections JoVE Encyclopedia of Experiments Archive

EDUCATION

JoVE Core JoVE Business JoVE Science Education JoVE Lab Manual Faculty Resource Center Faculty Site

Terms & Conditions of Use

Search research articles

Related Experiment Video

Updated: Sep 16, 2025

Author Spotlight: Enhancement of Salient Object Detection for Smart Grid Applications

Author Spotlight: Enhancement of Salient Object Detection for Smart Grid Applications

Published on: December 15, 2023

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

Yukang Fan¹, Kun Zhang², Bing Zheng³

¹School of Information Science and Technology, Hainan Normal University, Haikou, Hainan, 571158, China.

Scientific Reports

|July 6, 2025

Summary

Related Concept Videos

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by

Same author

Fluorine Positional Isomerism Enables H-Aggregation for High-Performance Semicrystalline Polymer Donors in Organic Solar Cells.

Small (Weinheim an der Bergstrasse, Germany)·2026

Same author

Low-resistance ohmic contacts for NbGeN<sub>3</sub> enabled by cold metals.

Physical chemistry chemical physics : PCCP·2026

Same author

Identification of G4-regulated immune-related drug targets for prostate cancer based on G4 screen and machine learning.

Frontiers in immunology·2026

Same author

GPNMB<sup>+</sup> macrophages promote osteogenic differentiation of nucleus pulposus cells through PDGF signaling in intervertebral disc degeneration.

Cell reports. Medicine·2026

Same author

Bound polyphenols from carrot dietary fiber delay aging in <i>Caenorhabditis elegans</i> through the IIS pathway and metabolic remodeling.

Food & function·2026

Same author

Synergistic Effect of Gradient Conductivity and Gradient Microstructures Enabled Ultrasensitive and Ultrabroad Linear Flexible Tactile Sensors.

Advanced science (Weinheim, Baden-Wurttemberg, Germany)·2026

This study introduces GCSA-ResNet, a deep learning model for enhanced malware detection. It improves accuracy and reduces false positives by analyzing visualized malware images more effectively.

Area of Science:

Cybersecurity
Artificial Intelligence
Computer Vision

Background:

Traditional malware detection methods struggle with increasing malware complexity and volume.
Deep learning offers potential but faces challenges in feature extraction and classification accuracy.
Existing attention mechanisms have limitations in capturing both local and global features.

Purpose of the Study:

To propose a novel deep learning model, GCSA-ResNet, for significantly improving malware detection performance.
To introduce the Global Channel-Spatial Attention (GCSA) module for enhanced feature extraction from visualized malware.
To address limitations in feature degradation and cross-family misclassification in current methods.

Main Methods:

Developed GCSA-ResNet by integrating the Global Channel-Spatial Attention (GCSA) module with the ResNet-50 architecture.

Keywords:

Attention mechanism Deep learning Feature fusion Malware detection Malware visualization

More Related Videos

DNA Virus Detection System Based on RPA-CRISPR/Cas12a-SPM and Deep Learning

DNA Virus Detection System Based on RPA-CRISPR/Cas12a-SPM and Deep Learning

Published on: May 10, 2024

Deep Neural Networks for Image-Based Dietary Assessment

Deep Neural Networks for Image-Based Dietary Assessment

Published on: March 13, 2021

Related Experiment Videos

Last Updated: Sep 16, 2025

Author Spotlight: Enhancement of Salient Object Detection for Smart Grid Applications

Author Spotlight: Enhancement of Salient Object Detection for Smart Grid Applications

Published on: December 15, 2023

DNA Virus Detection System Based on RPA-CRISPR/Cas12a-SPM and Deep Learning

DNA Virus Detection System Based on RPA-CRISPR/Cas12a-SPM and Deep Learning

Published on: May 10, 2024

Deep Neural Networks for Image-Based Dietary Assessment

Deep Neural Networks for Image-Based Dietary Assessment

Published on: March 13, 2021

The GCSA module collaboratively uses channel attention, channel shuffling, and spatial attention to capture texture and dependency features.

Employed a 7x7 convolutional kernel in spatial attention for modeling long-range spatial correlations.

Main Results:

GCSA-ResNet achieved over 98.50% accuracy on Malimg and Microsoft BIG 2015 datasets.
Demonstrated a performance improvement of more than 0.5% compared to baseline models.
Reduced false positive rates by 40-50% while maintaining stable precision, recall, and F1-scores.

Conclusions:

GCSA-ResNet effectively enhances malware detection by leveraging advanced attention mechanisms.
The model overcomes limitations of existing methods in feature degradation and cross-family misclassification.
The proposed approach offers a robust solution for identifying complex and evolving malware threats.