A Novel Machine Learning Approach for Android Malware Detection Based on the Co-Existence of Features

This paper proposes a machine learning model based on the co-existence of static features for Android malware detection. The proposed model assumes that Android malware requests an abnormal set of co-existed permissions and APIs in comparing to those requested by benign applications. To prove this a...

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Главные авторы:	Esraa Odat, Qussai M. Yaseen
Формат:	Artigo
Язык:	Inglês
Опубликовано:	IEEE 2023-01-01
Серии:	IEEE Access
Предметы:	Android co-existence FP-growth machine learning malware
Online-ссылка:	https://ieeexplore.ieee.org/document/10043652/
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