A Machine-learning Approach for Classifying and Categorizing Android Sources and Sinks

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Presented at NDSS 2014 by

Eric Bodden

Steven Arzt

Siegfried Rasthofer

In this paper we propose SUSI, a novel machine-learning guided approach for identifying and categorizing previously unknown privacy-sensitive sources and sinks directly from the code of any Android API (e.g., Android 4.3 or GoogleGlass). Our results improve both static and dynamic analysis tools in detecting malicious information flows more completely.