TaintDroid

TLDR

Today’s smartphone operating systems frequently fail to provide users with visibility into how third‑party applications collect and share their private data. The authors present TaintDroid, an efficient, system‑wide dynamic taint‑tracking and analysis system that simultaneously tracks multiple sources of sensitive data to address these privacy visibility gaps. TaintDroid achieves real‑time analysis by leveraging Android’s virtualized execution environment. TaintDroid incurs only 32% overhead on a CPU‑bound microbenchmark, negligible overhead on interactive apps, and in studies of 30 popular Android applications it identified misused private data in roughly two‑thirds of them, providing valuable input for users and security firms.

Abstract

Today’s smartphone operating systems frequently fail to provide users with visibility into how third-party applications collect and share their private data. We address these shortcomings with TaintDroid, an efficient, system-wide dynamic taint tracking and analysis system capable of simultaneously tracking multiple sources of sensitive data. TaintDroid enables realtime analysis by leveraging Android’s virtualized execution environment. TaintDroid incurs only 32% performance overhead on a CPU-bound microbenchmark and imposes negligible overhead on interactive third-party applications. Using TaintDroid to monitor the behavior of 30 popular third-party Android applications, in our 2010 study we found 20 applications potentially misused users’ private information; so did a similar fraction of the tested applications in our 2012 study. Monitoring the flow of privacy-sensitive data with TaintDroid provides valuable input for smartphone users and security service firms seeking to identify misbehaving applications.