POWERFUL: Mobile app fingerprinting via power analysis

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

doi:10.1109/INFOCOM.2017.8057232

POWERFUL: Mobile app fingerprinting via power analysis

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

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

35 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 language	English (US)
Title of host publication	INFOCOM 2017 - IEEE Conference on Computer Communications
Publisher	Institute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)	9781509053360
DOIs	https://doi.org/10.1109/INFOCOM.2017.8057232
State	Published - Oct 2 2017
Event	2017 IEEE Conference on Computer Communications, INFOCOM 2017 - Atlanta, United States Duration: May 1 2017 → May 4 2017

Publication series

Name	Proceedings - IEEE INFOCOM
ISSN (Print)	0743-166X

Other

Other	2017 IEEE Conference on Computer Communications, INFOCOM 2017
Country/Territory	United States
City	Atlanta
Period	5/1/17 → 5/4/17

ASJC Scopus subject areas

General Computer Science
Electrical and Electronic Engineering

Access to Document

10.1109/INFOCOM.2017.8057232

Cite this

Chen, Y, Jin, X, Sun, J, Zhang, R & Zhang, Y 2017, POWERFUL: Mobile app fingerprinting via power analysis. in INFOCOM 2017 - IEEE Conference on Computer Communications., 8057232, Proceedings - IEEE INFOCOM, Institute of Electrical and Electronics Engineers Inc., 2017 IEEE Conference on Computer Communications, INFOCOM 2017, Atlanta, United States, 5/1/17. https://doi.org/10.1109/INFOCOM.2017.8057232

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title = "POWERFUL: Mobile app fingerprinting via power analysis",

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.",

author = "Yimin Chen and Xiaocong Jin and Jingchao Sun and Rui Zhang and Yanchao Zhang",

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PY - 2017/10/2

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N2 - 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.

AB - 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.

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POWERFUL: Mobile app fingerprinting via power analysis

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