NDSS

Author(s): Siegfried Rasthofer, Steven Arzt, Eric Bodden

Download: Paper (PDF)

Date: 22 Feb 2014

Document Type: Briefing Papers

Additional Documents: Slides

Associated Event: NDSS Symposium 2014

Abstract:

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.