Skip to main content

Cross Pocket Gait Authentication Using Mobile Phone Based Accelerometer Sensor

  • Conference paper
  • First Online:

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 9520))

Abstract

Gait authentication using mobile phone based accelerometer sensors offers an implicit way of authenticating users to their mobile devices. This study explores gait authentication performance under a realistic scenario if gait template and gait test data belongs to left and right side front pocket of the trousers. To simulate this scenario, we used two identical (model, build, and vendor) Android mobile phones to record cross pocket biometric gait data from 35 participants (29 male and 6 female) in two different sessions. Both datasets (left and right pocket) are processed and segmented using the same approach. Our results show that biometric gait performance not only decreases over the time but it is also highly influenced by the placement of the mobile device or the sensor capturing gait data. High number of False Non Matches (FNMR) in cross pocket scenario indicate a significant asymmetry in leg muscle strength.

This is a preview of subscription content, log in via an institution.

Buying options

Chapter
USD   29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD   39.99
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD   54.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Learn about institutional subscriptions

References

  1. Derawi, M.O.: Smartphones and biometrics: gait and activity recognition. Ph.D. thesis, Gjøvik University College, November 2012

    Google Scholar 

  2. Gafurov, D.: Performance and security analysis of gait-based user authentication. Ph.D. thesis, Universitas Osloensis (2004)

    Google Scholar 

  3. Hintze, D., Findling, R.D., Muaaz, M., Scholz, S., Mayrhofer, R.: Diversity in locked and unlocked mobile device usage. In: Proceedings of the 2014 ACM International Joint Conference on Pervasive and Ubiquitous Computing: Adjunct Publication, UbiComp 2014 Adjunct, pp. 379–384. ACM, New York, NY, USA (2014)

    Google Scholar 

  4. Muaaz, M., Nickel, C.: Influence of different walking speeds and surfaces on accelerometer-based biometric gait recognition. In: 2012 35th International Conference on Telecommunications and Signal Processing (TSP), pp. 508–512 (2012)

    Google Scholar 

  5. Muaaz, M., Mayrhofer, R.: An analysis of different approaches to gait recognition using cell phone based accelerometers. In: Proceedings of International Conference on Advances in Mobile Computing and Multimedia, pp. 293–300. ACM (2013)

    Google Scholar 

  6. Muaaz, M., Mayrhofer, R.: Orientation independent cell phone based gait authentication. In: Proceedings of the 12th International Conference on Advances in Mobile Computing and Multimedia, MoMM 2014, pp. 161–164. ACM, New York, NY, USA (2014)

    Google Scholar 

  7. Nickel, C.: Accelerometer-based biometric gait recognition for authentication on smartphones. Ph.D. thesis, TU Darmstadt (June 2012)

    Google Scholar 

Download references

Acknowledgments

We gratefully acknowledge funding and support by the Christian Doppler Gesellschaft, A1 Telekom Austria AG, Drei-Banken-EDV GmbH, LG Nexera Business Solutions AG, and NXP Semiconductors Austria GmbH.

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Muhammad Muaaz .

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2015 Springer International Publishing Switzerland

About this paper

Cite this paper

Muaaz, M., Mayrhofer, R. (2015). Cross Pocket Gait Authentication Using Mobile Phone Based Accelerometer Sensor. In: Moreno-Díaz, R., Pichler, F., Quesada-Arencibia, A. (eds) Computer Aided Systems Theory – EUROCAST 2015. EUROCAST 2015. Lecture Notes in Computer Science(), vol 9520. Springer, Cham. https://doi.org/10.1007/978-3-319-27340-2_90

Download citation

  • DOI: https://doi.org/10.1007/978-3-319-27340-2_90

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-27339-6

  • Online ISBN: 978-3-319-27340-2

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics