AndroMD: An Android malware detection framework based on source code analysis and permission scanning

The rapid growth of Android-based mobile and IoT applications has significantly increased the attack surface for malicious actors. These adversaries often exploit apps and social engineering to deliver malware that compromises device security and user privacy. To address this ongoing threat, we pres...

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Auteurs principaux:	Arvind Prasad, Shalini Chandra, Wael Mohammad Alenazy, Gauhar Ali, Sajid Shah, Mohammed ElAffendi
Format:	Artigo
Langue:	Inglês
Publié:	Elsevier 2025-12-01
Collection:	Results in Engineering
Sujets:	Malware analysis Machine learning Feature selection Cybersecurity Android malware dataset
Accès en ligne:	http://www.sciencedirect.com/science/article/pii/S2590123025031068
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