Enhancing the Sustainability of Machine Learning-Based Malware Detection Techniques for Android Applications

Enhancing the Sustainability of Machine Learning-Based Malware Detection Techniques for Android Applications

The rapid increase in smartphone usage has led to a corresponding rise in malicious Android applications, making it important to develop efficient and sustainable malware detection methods that maintain high accuracy. This paper presents a two-stage machine learning approach aimed at improving both...

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Bibliographic Details
Main Authors:	Seyeon Park, Hojun Lee, Daeun Kim, Hyeun Jun Moon, Seong-Je Cho, Youngsup Hwang, Hyoil Han, Kyoungwon Suh
Format:	Article
Language:	English
Published:	IEEE 2025-01-01
Series:	IEEE Access
Subjects:	Android malware malware detection Random Forest model
Online Access:	https://ieeexplore.ieee.org/document/11023590/
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