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Due to the ever increasing amount and severity of attacks aimed at compromising smartphones in general, and Android devices in particular, much effort have been devoted in recent years to deal with such incidents. However, accurate detection of bad-intentioned Android apps still is an open challenge. As a follow-up step in an ongoing research, preset paper explores the selection of features for the characterization of Android-malware families. The idea is to select those features that are most relevant for characterizing malware families. In order to do that, an evolutionary algorithm is proposed to perform feature selection on the Drebin dataset, attaining interesting results on the most informative features for the characterization of representative families of existing Android malware.

Characterization of Android Malware Families by a Reduced Set of Static Features