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Unobtrusive User-Authentication on Mobile Phones Using Biometric Gait Recognition
Abstract
The need for more security on mobile devices is increasing with new functionalities and features made available. To improve the device security we propose gait recognition as a protection mechanism. Unlike previous work on gait recognition, which was based on the use of video sources, floor sensors or dedicated high-grade accelerometers, this paper reports the performance when the data is collected with a commercially available mobile device containing low-grade accelerometers. To be more specific, the used mobile device is the Google G1 phone containing the AK8976A embedded accelerometer sensor. The mobile device was placed at the hip on each volunteer to collect gait data. Preproccesing, cycle detection and recognition-analysis were applied to the acceleration signal. The performance of the system was evaluated having 51 volunteers and resulted in an equal error rate (EER) of 20%.
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Cites
The humanID gait challenge problem: data sets, performance, and analysis
Sarkar, S., Phillips, P. J., Liu, Z., Vega, I. R., Grother, P., & Bowyer, K. W. (2005) · IEEE Transactions on Pattern Analysis and Machine Intelligence · doi:10.1109/tpami.2005.39 · Cited by 1,133
Cited by
Frank, M., Biedert, R., Ma, E., Martinovic, I., & Song, D. (2013) · IEEE Transactions on Information Forensics and Security · doi:10.1109/tifs.2012.2225048 · Cited by 844
Cancelable Biometrics: A review
Patel, V. M., Ratha, N. K., & Chellappa, R. (2015) · IEEE Signal Processing Magazine · doi:10.1109/msp.2015.2434151 · Cited by 419
A review of biometric technology along with trends and prospects
Unar, J. A., Seng, W. C., & Abbasi, A. (2014) · Pattern Recognition · doi:10.1016/j.patcog.2014.01.016 · Cited by 404
HMOG: New Behavioral Biometric Features for Continuous Authentication of Smartphone Users
Sitova, Z., Sedenka, J., Yang, Q., Peng, G., Zhou, G., Gasti, P., & Balagani, K. S. (2016) · IEEE Transactions on Information Forensics and Security · doi:10.1109/tifs.2015.2506542 · Cited by 398
Inertial Sensor-Based Gait Recognition: A Review
Sprager, S., & Juric, M. (2015) · Sensors · doi:10.3390/s150922089 · Cited by 347
Metadata
- Authors
- Derawi, M. O., Nickel, C., Bours, P., & Busch, C.
- Venue
- 2010 Sixth International Conference on Intelligent Information Hiding and Multimedia Signal Processing
- Publisher
- IEEE
- Published
- 2010-10
- Pages
- 306-311
- OpenAlex
- W2070381776
- Cited by
- 343
- References
- 1
- FWCI
- 42.05
- Type
- conference paper
- Language
- en
- Open access
- closed
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- Derawi, M. O., Nickel, C., Bours, P., & Busch, C. (2010). Unobtrusive User-Authentication on Mobile Phones Using Biometric Gait Recognition. 2010 Sixth International Conference on Intelligent Information Hiding and Multimedia Signal Processing. https://doi.org/10.1109/iihmsp.2010.83
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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
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