Continuous user authentication in smartphones using gait analysis

M. P. Mufandaidza; T. D. Ramotsoela; G. P. Hancke

doi:10.1109/IECON.2018.8591193

Continuous user authentication in smartphones using gait analysis

M. P. Mufandaidza
, T. D. Ramotsoela^*
, G. P. Hancke

^*Corresponding author for this work

Department of Computer Science

Research output: Chapters, Conference Papers, Creative and Literary Works › RGC 32 - Refereed conference paper (with host publication) › peer-review

18 Citations (Scopus)

Abstract

This paper presents the development a smartphone user authentication system which takes advantage of the device's pre-existing hardware. The authentication was based on a smartphone user's gait pattern which is a biometric feature. If the authentication outcome is positive the authentication process continues uninterrupted in the background. If the authentication fails, the device's location information should be sent to a predetermined email address to notify the authorized user of the device's whereabouts. While the performance of the proposed scheme is promising, it does need to be improved in order for the system to become practically viable.

Original language	English
Title of host publication	Proceedings
Subtitle of host publication	IECON 2018 - 44th Annual Conference of the IEEE Industrial Electronics Society
Publisher	IEEE
Pages	4656-4661
ISBN (Electronic)	978-1-5090-6684-1
DOIs	https://doi.org/10.1109/IECON.2018.8591193
Publication status	Published - Oct 2018
Event	44th Annual Conference of the IEEE Industrial Electronics Society, IECON 2018 - Washington, United States Duration: 20 Oct 2018 → 23 Oct 2018 https://ieeexplore.ieee.org/xpl/conhome/8560606/proceeding

Publication series

Name	Proceedings: IECON 2018 - 44th Annual Conference of the IEEE Industrial Electronics Society

Conference

Conference	44th Annual Conference of the IEEE Industrial Electronics Society, IECON 2018
Place	United States
City	Washington
Period	20/10/18 → 23/10/18
Internet address	https://ieeexplore.ieee.org/xpl/conhome/8560606/proceeding

Research Keywords

Authentication
Dynamic time warping
Gait
Neural network
Smartphone

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10.1109/IECON.2018.8591193

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Mufandaidza, M. P., Ramotsoela, T. D., & Hancke, G. P. (2018). Continuous user authentication in smartphones using gait analysis. In Proceedings: IECON 2018 - 44th Annual Conference of the IEEE Industrial Electronics Society (pp. 4656-4661). Article 8591193 (Proceedings: IECON 2018 - 44th Annual Conference of the IEEE Industrial Electronics Society). IEEE. https://doi.org/10.1109/IECON.2018.8591193

@inproceedings{d011fb78e2844148af6fac2ad3c2e1ee,

title = "Continuous user authentication in smartphones using gait analysis",

abstract = "This paper presents the development a smartphone user authentication system which takes advantage of the device's pre-existing hardware. The authentication was based on a smartphone user's gait pattern which is a biometric feature. If the authentication outcome is positive the authentication process continues uninterrupted in the background. If the authentication fails, the device's location information should be sent to a predetermined email address to notify the authorized user of the device's whereabouts. While the performance of the proposed scheme is promising, it does need to be improved in order for the system to become practically viable.",

keywords = "Authentication, Dynamic time warping, Gait, Neural network, Smartphone",

author = "Mufandaidza, \{M. P.\} and Ramotsoela, \{T. D.\} and Hancke, \{G. P.\}",

year = "2018",

month = oct,

doi = "10.1109/IECON.2018.8591193",

language = "English",

series = "Proceedings: IECON 2018 - 44th Annual Conference of the IEEE Industrial Electronics Society",

publisher = "IEEE",

pages = "4656--4661",

booktitle = "Proceedings",

address = "United States",

note = "44th Annual Conference of the IEEE Industrial Electronics Society, IECON 2018 ; Conference date: 20-10-2018 Through 23-10-2018",

url = "https://ieeexplore.ieee.org/xpl/conhome/8560606/proceeding",

}

Mufandaidza, MP, Ramotsoela, TD & Hancke, GP 2018, Continuous user authentication in smartphones using gait analysis. in Proceedings: IECON 2018 - 44th Annual Conference of the IEEE Industrial Electronics Society., 8591193, Proceedings: IECON 2018 - 44th Annual Conference of the IEEE Industrial Electronics Society, IEEE, pp. 4656-4661, 44th Annual Conference of the IEEE Industrial Electronics Society, IECON 2018, Washington, District of Columbia, United States, 20/10/18. https://doi.org/10.1109/IECON.2018.8591193

Continuous user authentication in smartphones using gait analysis. / Mufandaidza, M. P.; Ramotsoela, T. D.; Hancke, G. P.
Proceedings: IECON 2018 - 44th Annual Conference of the IEEE Industrial Electronics Society. IEEE, 2018. p. 4656-4661 8591193 (Proceedings: IECON 2018 - 44th Annual Conference of the IEEE Industrial Electronics Society).

Research output: Chapters, Conference Papers, Creative and Literary Works › RGC 32 - Refereed conference paper (with host publication) › peer-review

TY - GEN

T1 - Continuous user authentication in smartphones using gait analysis

AU - Mufandaidza, M. P.

AU - Ramotsoela, T. D.

AU - Hancke, G. P.

PY - 2018/10

Y1 - 2018/10

N2 - This paper presents the development a smartphone user authentication system which takes advantage of the device's pre-existing hardware. The authentication was based on a smartphone user's gait pattern which is a biometric feature. If the authentication outcome is positive the authentication process continues uninterrupted in the background. If the authentication fails, the device's location information should be sent to a predetermined email address to notify the authorized user of the device's whereabouts. While the performance of the proposed scheme is promising, it does need to be improved in order for the system to become practically viable.

AB - This paper presents the development a smartphone user authentication system which takes advantage of the device's pre-existing hardware. The authentication was based on a smartphone user's gait pattern which is a biometric feature. If the authentication outcome is positive the authentication process continues uninterrupted in the background. If the authentication fails, the device's location information should be sent to a predetermined email address to notify the authorized user of the device's whereabouts. While the performance of the proposed scheme is promising, it does need to be improved in order for the system to become practically viable.

KW - Authentication

KW - Dynamic time warping

KW - Gait

KW - Neural network

KW - Smartphone

UR - https://www.scopus.com/pages/publications/85061523934

UR - https://www.scopus.com/pages/publications/85061523934#tab=impact

U2 - 10.1109/IECON.2018.8591193

DO - 10.1109/IECON.2018.8591193

M3 - RGC 32 - Refereed conference paper (with host publication)

T3 - Proceedings: IECON 2018 - 44th Annual Conference of the IEEE Industrial Electronics Society

SP - 4656

EP - 4661

BT - Proceedings

PB - IEEE

T2 - 44th Annual Conference of the IEEE Industrial Electronics Society, IECON 2018

Y2 - 20 October 2018 through 23 October 2018

ER -

Continuous user authentication in smartphones using gait analysis

Abstract

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Research Keywords

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