Similarity-based Android malware detection using Hamming distance of static binary features

In this paper, we develop four malware detection methods using Hamming distance to find similarity between samples which are first nearest neighbors (FNN), all nearest neighbors (ANN), weighted all nearest neighbors (WANN), and k-medoid based nearest neighbors (KMNN). In our proposed methods, we can...

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Veröffentlicht in:	Future generation computer systems Jg. 105; S. 230 - 247
Hauptverfasser:	Taheri, Rahim, Ghahramani, Meysam, Javidan, Reza, Shojafar, Mohammad, Pooranian, Zahra, Conti, Mauro
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	Elsevier B.V 01.04.2020
Schlagworte:	Android Clustering Hamming distance K-nearest neighbor (KNN) Malware detection Static analysis Hamming distance Clustering Malware detection K-nearest neighbor (KNN) Static analysis Android
ISSN:	0167-739X
Online-Zugang:	Volltext
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