Multimodal Deep Learning for Android Malware Classification

Multimodal Deep Learning for Android Malware Classification

This study investigates the integration of diverse data modalities within deep learning ensembles for Android malware classification. Android applications can be represented as binary images and function call graphs, each offering complementary perspectives on the executable. We synthesise these mod...

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Bibliographic Details
Main Authors: James Arrowsmith, Teo Susnjak, Julian Jang-Jaccard
Format: Article
Language:English
Published: MDPI AG 2025-02-01
Series:Machine Learning and Knowledge Extraction
Subjects:
multimodal deep learning for Android malware detection
enhanced malware analysis
graph neural networks
function call graphs (FCG)
efficient multimodal late fusion
CNN GNN Ensemble
Online Access:https://www.mdpi.com/2504-4990/7/1/23
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