Evaluation of Android Malware Detection Based on System Calls (CROSBI ID 635338)
Prilog sa skupa u zborniku | izvorni znanstveni rad | međunarodna recenzija
Podaci o odgovornosti
Dimjašević, Marko ; Atzeni, Simone ; Ugrina, Ivo ; Rakamarić, Zvonimir
engleski
Evaluation of Android Malware Detection Based on System Calls
With Android being the most widespread mobile platform, protecting it against malicious applications is essential. Android users typically install applications from large remote repositories, which provides ample opportunities for malicious newcomers. In this paper, we evaluate a few techniques for detecting malicious Android applications on a repository level. The techniques perform automatic classification based on tracking system calls while applications are executed in a sandbox environment. We implemented the techniques in the MALINE tool, and performed extensive empirical evaluation on a suite of around 12, 000 applications. The evaluation considers the size and type of inputs used in analyses. We show that simple and relatively small inputs result in an overall detection accuracy of 93% with a 5% benign application classification error, while results are improved to a 96% detection accuracy with upsampling. Finally, we show that even simplistic feature choices are effective, suggesting that more heavyweight approaches should be thoroughly (re)evaluated.
Android; Malware; System Call
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Podaci o prilogu
1-8.
2016.
objavljeno
Podaci o matičnoj publikaciji
Proceedings of the 2016 ACM on International Workshop on Security And Privacy Analytics
New York (NY): The Association for Computing Machinery (ACM)
978-1-4503-4077-9
Podaci o skupu
IWSPA ’16 (2016 ACM on International Workshop on Security And Privacy Analytics)
predavanje
09.04.2016-11.04.2016
New Orleans (LA), Sjedinjene Američke Države