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StubDroid: automatic inference of precise data-flow summaries for the android framework

Steven Arzt, Eric Bodden

Abstract

Smartphone users suffer from insufficient information on how commercial as well as malicious apps handle sensitive data stored on their phones. Automated taint analyses address this problem by allowing users to detect and investigate how applications access and handle this data. A current problem with virtually all those analysis approaches is, though, that they rely on explicit models of the Android runtime library. In most cases, the existence of those models is taken for granted, despite the fact that the models are hard to come by: Given the size and evolution speed of a modern smartphone operating system it is prohibitively expensive to derive models manually from code or documentation.

BibTeX
@inproceedings{Arzt-Bodden:ICSE16,
  author    = {Steven Arzt and
               Eric Bodden},
  title     = {{StubDroid:} automatic inference of precise data-flow summaries for the android framework},
  booktitle = {ICSE},
  pages     = {725--735},
  publisher = {{ACM}},
  year      = {2016},
}

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