DocumentCode :
1846941
Title :
Instance-based anomaly method for Android malware detection
Author :
Sanz, Borja ; Santos, Igor ; Ugarte-Pedrero, Xabier ; Laorden, Carlos ; Nieves, Javier ; Bringas, Pablo G.
Author_Institution :
S3Lab, University of Deusto, Avenida de las Universidades 24, Bilbao, Spain
fYear :
2013
fDate :
29-31 July 2013
Firstpage :
1
Lastpage :
8
Abstract :
The usage of mobile phones has increased in our lives because they offer nearly the same functionality as a personal computer. Besides, the number of applications available for Android-based mobile devices has increased. Android application distribution is based on a centralized market where the developers can upload and sell their applications. However, as it happens with any popular service, it is prone to misuse and, in particular, malware writers can use this market to upload their malicious creations. In this paper, we propose a new method that, based upon several features that are extracted from the AndroidManifest file of the legitimate applications, builds an anomaly detection system able to detect malware.
Keywords :
Androids; Feature extraction; Humanoid robots; Malware; Smart phones; Software; Android; Malware; Security;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Security and Cryptography (SECRYPT), 2013 International Conference on
Conference_Location :
Reykjavik, Iceland
Type :
conf
Filename :
7223189
Link To Document :
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