4.3 Article

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

Journal

ACM TRANSACTIONS ON COMPUTER SYSTEMS
Volume 32, Issue 2, Pages -

Publisher

ASSOC COMPUTING MACHINERY
DOI: 10.1145/2619091

Keywords

Design; Security; Performance; Information-flow tracking; privacy monitoring; smartphones; mobile apps

Funding

  1. Engineering Research Center of Excellence Program of Korea Ministry of Science, ICT & Future Planning (MSIP)/National Research Foundation of Korea (NRF) [NRF-2008-0062609]
  2. Direct For Computer & Info Scie & Enginr
  3. Division Of Computer and Network Systems [0905447] Funding Source: National Science Foundation
  4. Direct For Computer & Info Scie & Enginr
  5. Division Of Computer and Network Systems [1228700] Funding Source: National Science Foundation
  6. National Research Foundation of Korea [2008-0062609] Funding Source: Korea Institute of Science & Technology Information (KISTI), National Science & Technology Information Service (NTIS)

Ask authors/readers for more resources

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.

Authors

I am an author on this paper
Click your name to claim this paper and add it to your profile.

Reviews

Primary Rating

4.3
Not enough ratings

Secondary Ratings

Novelty
-
Significance
-
Scientific rigor
-
Rate this paper

Recommended

No Data Available
No Data Available