TaintDroid: an information flow tracking system for real-time privacy monitoring on smartphones

  • Authors:
  • William Enck;Peter Gilbert;Byung-Gon Chun;Landon P. Cox;Jaeyeon Jung;Patrick McDaniel;Anmol N. Sheth

  • Affiliations:
  • North Carolina State University;Duke University;Seoul National University;Duke University;Microsoft Research;Pennsylvania State University;Technicolor Research

  • Venue:
  • Communications of the ACM
  • Year:
  • 2014

Quantified Score

Hi-index 48.22

Visualization

Abstract

Today's smartphone operating systems frequently fail to provide users with adequate control over and visibility into how third-party applications use their privacy-sensitive data. We address these shortcomings with TaintDroid, an efficient, systemwide dynamic taint tracking and analysis system capable of simultaneously tracking multiple sources of sensitive data. TaintDroid provides real-time analysis by leveraging Android's virtualized execution environment. Using TaintDroid to monitor the behavior of 30 popular third-party Android applications, we found 68 instances of misappropriation of users' location and device identification information across 20 applications. Monitoring sensitive data with TaintDroid provides informed use of third-party applications for phone users and valuable input for smartphone security service firms seeking to identify misbehaving applications.