MAMA: MANIFEST ANALYSIS FOR MALWARE DETECTION IN ANDROID
Borja Sanz, Igor Santos, Carlos Laorden, Xabier Ugarte-Pedrero, Javier Nieves, Pablo G. Bringas, Gonzalo Álvarez Marañón
Abstract
Borja Sanz, Igor Santos, Carlos Laorden, Xabier Ugarte-Pedrero, Javier Nieves, Pablo G. Bringas, Gonzalo Álvarez Marañón
Abstract
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.
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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.
Key concepts: Malware, Android (operating system), Upload, Computer science, Android malware, Computer security, Android application, Cryptovirology