TaintDroid: An Information-Flow Tracking System for Realtime Privacy Monitoring on Smartphones

  • William Enck ,
  • Peter Gilbert ,
  • Seungyeop Han ,
  • Vasant Tendulkar ,
  • Byung-Gon Chun ,
  • ,
  • Jaeyeon Jung ,
  • Patrick McDaniel ,
  • Anmol N. Sheth

Transactions on Computer Systems |

SIGOPS Hall of Fame Award

Publication

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.