DroidGen: Constraint-based and Data-Driven Policy Generation for Android

Mohamed Nassim Seghir; David Aspinall

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arXiv · 1612.07586

DroidGen: Constraint-based and Data-Driven Policy Generation for Android

Mohamed Nassim Seghir·David Aspinall

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Abstract

We present DroidGen a tool for automatic anti-malware policy inference. DroidGen employs a data-driven approach: it uses a training set of malware and benign applications and makes call to a constraint solver to generate a policy under which a maximum of malware is excluded and a maximum of benign applications is allowed. Preliminary results are encouraging. We are able to automatically generate a policy which filters out 91% of the tested Android malware. Moreover, compared to black-box machine learning classifiers, our method has the advantage of generating policies in a declarative readable format. We illustrate our approach, describe its implementation and report on the preliminary results.

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BibTeX RIS

Mohamed Nassim Seghir, David Aspinall. 2016-12-22. DroidGen: Constraint-based and Data-Driven Policy Generation for Android. https://arxiv.org/abs/1612.07586

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