Explaining Black-box Android Malware Detection

9 Mar 2018Marco MelisDavide MaiorcaBattista BiggioGiorgio GiacintoFabio Roli

Machine-learning models have been recently used for detecting malicious Android applications, reporting impressive performances on benchmark datasets, even when trained only on features statically extracted from the application, such as system calls and permissions. However, recent findings have highlighted the fragility of such in-vitro evaluations with benchmark datasets, showing that very few changes to the content of Android malware may suffice to evade detection... (read more)

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