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ACM HotMobile 2013 poster: leveraging imperfections of sensors for fingerprinting smartphones

Published: 07 November 2013 Publication History

Abstract

Device fingerprinting, similar to that of humans, if done well, can provide a convenient form of identification. In this poster, we explore whether constituent hardware sensors like accelerometers and gyroscopes of different smartphones can be exploited to fingerprint a smartphone. We observe that the readings of these sensors exhibit diverse features for different smartphones consistently when subjected to the same action.

References

[1]
ANDREJAIC, M. Mems accelerometers. Seminar (March 2008).
[2]
HILLMAN, D. C., AND TULKOFF, C. Manufacturing and Reliability Challenges With QFN. SMTA DC Chapter 45, 1 (February 2009).
[3]
JASON FRANKLIN ET AL. Passive Data Link Layer 802.11Wireless Device Driver Fingerprinting. In USENIX Security (August 2006).

Cited By

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  • (2022)Continuous Nonintrusive Mobile Device Soft Keyboard Biometric AuthenticationCryptography10.3390/cryptography60200146:2(14)Online publication date: 23-Mar-2022
  • (2022)Overlay-Based Android Malware Detection at Market Scales: Systematically Adapting to the New Technological LandscapeIEEE Transactions on Mobile Computing10.1109/TMC.2021.307943321:12(4488-4501)Online publication date: 1-Dec-2022
  • (2020)Systematically Landing Machine Learning onto Market-Scale Mobile Malware DetectionIEEE Transactions on Parallel and Distributed Systems10.1109/TPDS.2020.3046092(1-1)Online publication date: 2020
  • Show More Cited By

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Information & Contributors

Information

Published In

cover image ACM SIGMOBILE Mobile Computing and Communications Review
ACM SIGMOBILE Mobile Computing and Communications Review  Volume 17, Issue 3
July 2013
35 pages
ISSN:1559-1662
EISSN:1931-1222
DOI:10.1145/2542095
Issue’s Table of Contents

Publisher

Association for Computing Machinery

New York, NY, United States

Publication History

Published: 07 November 2013
Published in SIGMOBILE Volume 17, Issue 3

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Cited By

View all
  • (2022)Continuous Nonintrusive Mobile Device Soft Keyboard Biometric AuthenticationCryptography10.3390/cryptography60200146:2(14)Online publication date: 23-Mar-2022
  • (2022)Overlay-Based Android Malware Detection at Market Scales: Systematically Adapting to the New Technological LandscapeIEEE Transactions on Mobile Computing10.1109/TMC.2021.307943321:12(4488-4501)Online publication date: 1-Dec-2022
  • (2020)Systematically Landing Machine Learning onto Market-Scale Mobile Malware DetectionIEEE Transactions on Parallel and Distributed Systems10.1109/TPDS.2020.3046092(1-1)Online publication date: 2020
  • (2020)User-Silicon Entangled Mobile Identity AuthenticationJournal of Hardware and Systems Security10.1007/s41635-020-00098-7Online publication date: 2-Jul-2020
  • (2019)Understanding and Detecting Overlay-based Android Malware at Market ScalesProceedings of the 17th Annual International Conference on Mobile Systems, Applications, and Services10.1145/3307334.3326094(168-179)Online publication date: 12-Jun-2019
  • (2018)Design and Implementation of Android Container Monitoring Server and AgentInformation Security Applications10.1007/978-3-319-93563-8_14(162-172)Online publication date: 23-Jun-2018
  • (2015)Characterizing Composite User-Device Touchscreen Physical Unclonable Functions (PUFs) for Mobile Device AuthenticationProceedings of the 5th International Workshop on Trustworthy Embedded Devices10.1145/2808414.2808418(3-13)Online publication date: 16-Oct-2015
  • (2015)Mobile device fingerprinting considered harmful for risk-based authenticationProceedings of the Eighth European Workshop on System Security10.1145/2751323.2751329(1-6)Online publication date: 21-Apr-2015
  • (2014)Rage against the virtual machineProceedings of the Seventh European Workshop on System Security10.1145/2592791.2592796(1-6)Online publication date: 13-Apr-2014

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