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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Vydané v:	Future generation computer systems Ročník 105; s. 230 - 247
Hlavní autori:	Taheri, Rahim, Ghahramani, Meysam, Javidan, Reza, Shojafar, Mohammad, Pooranian, Zahra, Conti, Mauro
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	Elsevier B.V 01.04.2020
Predmet:	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
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