POWERFUL: Mobile app fingerprinting via power analysis

Yimin Chen, Xiaocong Jin, Jingchao Sun, Rui Zhang, Yanchao Zhang

Research output: Chapter in Book/Report/Conference proceedingConference contribution

15 Scopus citations

Abstract

Which apps a mobile user has and how they are used can disclose significant private information about the user. In this paper, we present the design and evaluation of POWERFUL, a new attack which can fingerprint sensitive mobile apps (or infer sensitive app usage) by analyzing the power consumption profiles on Android devices. POWERFUL works on the observation that distinct apps and their different usage patterns all lead to distinguishable power consumption profiles. Since the power profiles on Android devices require no permission to access, POWERFUL is very difficult to detect and can pose a serious threat against user privacy. Extensive experiments involving popular and sensitive apps in Google Play Store show that POWERFUL can identify the app used at any particular time with accuracy up to 92.9%, demonstrating the feasibility of POWERFUL.

Original languageEnglish (US)
Title of host publicationINFOCOM 2017 - IEEE Conference on Computer Communications
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781509053360
DOIs
StatePublished - Oct 2 2017
Event2017 IEEE Conference on Computer Communications, INFOCOM 2017 - Atlanta, United States
Duration: May 1 2017May 4 2017

Publication series

NameProceedings - IEEE INFOCOM
ISSN (Print)0743-166X

Other

Other2017 IEEE Conference on Computer Communications, INFOCOM 2017
Country/TerritoryUnited States
CityAtlanta
Period5/1/175/4/17

ASJC Scopus subject areas

  • Computer Science(all)
  • Electrical and Electronic Engineering

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