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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Hlavní autoři:	Seyeon Park, Hojun Lee, Daeun Kim, Hyeun Jun Moon, Seong-Je Cho, Youngsup Hwang, Hyoil Han, Kyoungwon Suh
Médium:	Artigo
Jazyk:	Inglês
Vydáno:	IEEE 2025-01-01
Edice:	IEEE Access
Témata:	Android malware malware detection Random Forest model
On-line přístup:	https://ieeexplore.ieee.org/document/11023590/
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