Framework for malware analysis in Android

Christian Urcuqui-López, Andrés Navarro Cadavid


Android is a open source operating system with more than a billion of users, including all kind of devices (cell phones, TV, smart watch, etc). The amount of sensitive data “using” this technologies has increased the cyber criminals interest to develop tools and techniques to acquire that information or to disrupt the device's smooth operation. Despite several solutions are able to guarantee an adequate level of security, day by day the hackers skills grows up (because of their growing experience), what means a permanent challenge for security tools developers. As a response, several members of the research community are using artificial intelligence tools for Android security, particularly machine learning techniques to classify between healthy and malicious apps; from an analytic review of those works, this paper propose a static analysis framework and machine learning to do that classification.


Framework; machine learning; security; Google; malware.

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