research-article

Unobtrusive gait verification for mobile phones

Authors:

Jonathan Huang,

Tanwistha Saha,

Lama NachmanAuthors Info & Claims

ISWC '14: Proceedings of the 2014 ACM International Symposium on Wearable Computers

Pages 91 - 98

https://doi.org/10.1145/2634317.2642868

Published: 13 September 2014 Publication History

Abstract

Continuously and unobtrusively identifying the phone's owner using accelerometer sensing and gait analysis has a great potential to improve user experience on the go. However, a number of challenges, including gait modeling and training data acquisition, must be addressed before unobtrusive gait verification is practical. In this paper, we describe a gait verification system for mobile phone without any assumption of body placement or device orientation. Our system uses a combination of supervised and unsupervised learning techniques to verify the user continuously and automatically learn unseen gait pattern from the user over time. We demonstrate that it is capable of recognizing the user in natural settings. We also investigated an unobtrusive training method that makes it feasible to acquire training data without explicit user annotation.

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Cited By

Ying JZhu TLiu QXiong CWeng ZChen TFu LLv MWu HWang TChen Y(2024)TrapCog: An Anti-Noise, Transferable, and Privacy-Preserving Real-Time Mobile User Authentication System With High AccuracyIEEE Transactions on Mobile Computing10.1109/TMC.2023.326507123:4(2832-2848)Online publication date: Apr-2024
https://doi.org/10.1109/TMC.2023.3265071
Salvador-Ortega IVivaracho-Pascual CSimon-Hurtado A(2023)A New Post-Processing Proposal for Improving Biometric Gait Recognition Using Wearable DevicesSensors10.3390/s2303105423:3(1054)Online publication date: 17-Jan-2023
https://doi.org/10.3390/s23031054
Weng ZWu SWang QZhu T(2023)Enhancing Sensor-Based Mobile User Authentication in a Complex Environment by Deep LearningMathematics10.3390/math1117370811:17(3708)Online publication date: 29-Aug-2023
https://doi.org/10.3390/math11173708
Show More Cited By

Index Terms

Unobtrusive gait verification for mobile phones
1. Computing methodologies
  1. Machine learning
2. Human-centered computing
  1. Human computer interaction (HCI)

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Published In

cover image ACM Conferences

ISWC '14: Proceedings of the 2014 ACM International Symposium on Wearable Computers

September 2014

154 pages

ISBN:9781450329699

DOI:10.1145/2634317

General Chair:
Lucy Dunne
University of Minnesota Research
,
Program Chairs:
Tom Martin
Virginia Tech
,
Michael Beigl
Karlsruhe Institute of Technology, DE

Copyright © 2014 ACM.

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Publication History

Published: 13 September 2014

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UbiComp '14

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UbiComp '14: The 2014 ACM Conference on Ubiquitous Computing

September 13 - 17, 2014

Washington, Seattle

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Overall Acceptance Rate 38 of 196 submissions, 19%

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Cited By

Ying JZhu TLiu QXiong CWeng ZChen TFu LLv MWu HWang TChen Y(2024)TrapCog: An Anti-Noise, Transferable, and Privacy-Preserving Real-Time Mobile User Authentication System With High AccuracyIEEE Transactions on Mobile Computing10.1109/TMC.2023.326507123:4(2832-2848)Online publication date: Apr-2024
https://doi.org/10.1109/TMC.2023.3265071
Salvador-Ortega IVivaracho-Pascual CSimon-Hurtado A(2023)A New Post-Processing Proposal for Improving Biometric Gait Recognition Using Wearable DevicesSensors10.3390/s2303105423:3(1054)Online publication date: 17-Jan-2023
https://doi.org/10.3390/s23031054
Weng ZWu SWang QZhu T(2023)Enhancing Sensor-Based Mobile User Authentication in a Complex Environment by Deep LearningMathematics10.3390/math1117370811:17(3708)Online publication date: 29-Aug-2023
https://doi.org/10.3390/math11173708
Song WJia HWang MWu YXue WChou CHu JHu W(2023) Pistis : Replay Attack and Liveness Detection for Gait-Based User Authentication System on Wearable Devices Using Vibration IEEE Internet of Things Journal10.1109/JIOT.2022.323138110:9(8155-8171)Online publication date: 1-May-2023
https://doi.org/10.1109/JIOT.2022.3231381
Ji RLi JHe WRen JJiang X(2023)Dual-Stream Siamese Vision Transformer With Mutual Attention For Radar Gait VerificationICASSP 2023 - 2023 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)10.1109/ICASSP49357.2023.10095141(1-5)Online publication date: 4-Jun-2023
https://doi.org/10.1109/ICASSP49357.2023.10095141
Nassi BShams JRokach LElovici Y(2022)Virtual Breathalyzer: Towards the Detection of Intoxication Using Motion Sensors of Commercial Wearable DevicesSensors10.3390/s2209358022:9(3580)Online publication date: 8-May-2022
https://doi.org/10.3390/s22093580
Zhu TWeng ZSong QChen YLiu QChen YLv MChen T(2022)EspialCog: General, Efficient and Robust Mobile User Implicit Authentication in Noisy EnvironmentIEEE Transactions on Mobile Computing10.1109/TMC.2020.301249121:2(555-572)Online publication date: 1-Feb-2022
https://doi.org/10.1109/TMC.2020.3012491
Wu CHe KChen JZhao ZDu R(2022)Toward Robust Detection of Puppet Attacks via Characterizing Fingertip-Touch BehaviorsIEEE Transactions on Dependable and Secure Computing10.1109/TDSC.2021.311655219:6(4002-4018)Online publication date: 1-Nov-2022
https://doi.org/10.1109/TDSC.2021.3116552
Xu WXue WLin QLan GFeng XWei BLuo CLi WZomaya A(2022)PrivGait: An Energy-Harvesting-Based Privacy-Preserving User-Identification System by Gait AnalysisIEEE Internet of Things Journal10.1109/JIOT.2021.30896189:22(22048-22060)Online publication date: 15-Nov-2022
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Stragapede GVera-Rodriguez RTolosana RMorales AAcien ALan G(2022)Mobile Passive Authentication through Touchscreen and Background Sensor Data2022 International Workshop on Biometrics and Forensics (IWBF)10.1109/IWBF55382.2022.9794524(1-6)Online publication date: 20-Apr-2022
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