MAMA: MANIFEST ANALYSIS FOR MALWARE DETECTION IN ANDROID

被引：63

作者：

Sanz, Borja ^{[1
]}

Santos, Igor ^{[1
]}

Laorden, Carlos ^{[1
]}

Ugarte-Pedrero, Xabier ^{[1
]}

Nieves, Javier ^{[1
]}

Bringas, Pablo G. ^{[1
]}

Alvarez Maranon, Gonzalo ^{[2
]}

机构：

[1] Univ Deusto, S3Lab, Bilbao 48007, Spain

[2] CSIC, Inst Fis Aplicada, Madrid, Spain

来源：

CYBERNETICS AND SYSTEMS | 2013年 / 44卷 / 6-7期

关键词：

Android; machine learning; malware;

D O I：

10.1080/01969722.2013.803889

中图分类号：

TP3 [计算技术、计算机技术];

学科分类号：

0812 ;

摘要：

The use of mobile phones has increased because they offer nearly the same functionality as a personal computer. In addition, the number of applications available for Android-based mobile devices has increased. Google offers programmers the opportunity to upload and sell applications in the Android Market, but malware writers upload their malicious code there. In light of this background, we present here manifest analysis for malware detection in Android (MAMA), a new method that extracts several features from the Android manifest of the applications to build machine learning classifiers and detect malware.

引用

页码：469 / 488

页数：20

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