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Mobiles and Wearables: Owner Biometrics and Authentication

Published: 07 June 2016 Publication History

Abstract

We discuss the design and development of HCI models for authentication based on gait and gesture that can be supported by mobile and wearable equipment. The paper proposes to use such biometric behavioral traits for partially transparent and continuous authentication by means of behavioral patterns.

References

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Kanev, K., Kamiya, N., Mirenkov, N., Kanda, G., Takagi, A., Adaptive E-learning Applications with Transparent User Identification, In Proc HC'07, 13--15, 2007, pp. 25--30.
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Kanev, K., Kimura, S., Collaborative Learning in Dynamic Group Environments, Book chapter in "Distance Education Environments and Emerging Software Systems: new Technologies", Qun Jin (Ed.), IGI Global, 2011, pp. 1--14.
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J. Galbally-Herrero, J. Fierrez-Aguilar, J. D. Rodriguez-gonzalez, F. Alonso-Fernandez, J. Ortega-Garcia and M. Tapiador, "On the Vulnerability of Fingerprint Verification Systems to Fake Fingerprints Attacks," Proc. ICCST'06, pp. 130--136, IEEE, 2006.
[4]
De Marsico, M., & Mecca, A. (2015, September). Biometric Walk Recognizer. In Proc.-ICIAP 2015 Workshops (pp. 19--26). Springer International Publishing.
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Guerra-Casanova, J., Sánchez-Ávila, C., Bailador, G., & de Santos Sierra, A. (2012). Authentication in mobile devices through hand gesture recognition. International Journal of Information Security, 11(2), 65--83.
[6]
Kanev, K., De Marsico, M., Bottoni, P., A Human Computer Interactions Framework for Biometric User Identification, Jap. Journal of Applied Physics Conf. Proc., Vol. 4, 2016, 011601(1-6).

Cited By

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  • (2024)User gait biometrics in smart ambient applications through wearable accelerometer signals: an analysis of the influence of training setup on recognition accuracyJournal of Ambient Intelligence and Humanized Computing10.1007/s12652-024-04790-215:7(2967-2979)Online publication date: 15-Apr-2024
  1. Mobiles and Wearables: Owner Biometrics and Authentication

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    Published In

    cover image ACM Conferences
    AVI '16: Proceedings of the International Working Conference on Advanced Visual Interfaces
    June 2016
    400 pages
    ISBN:9781450341318
    DOI:10.1145/2909132
    Permission to make digital or hard copies of part or all 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 third-party components of this work must be honored. For all other uses, contact the Owner/Author.

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    Association for Computing Machinery

    New York, NY, United States

    Publication History

    Published: 07 June 2016

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    Author Tags

    1. User identification
    2. continuous biometric input
    3. mobile motion tracking
    4. transparent authentication
    5. wearable monitoring

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    AVI '16

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    AVI '16 Paper Acceptance Rate 20 of 96 submissions, 21%;
    Overall Acceptance Rate 128 of 490 submissions, 26%

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    • (2024)User gait biometrics in smart ambient applications through wearable accelerometer signals: an analysis of the influence of training setup on recognition accuracyJournal of Ambient Intelligence and Humanized Computing10.1007/s12652-024-04790-215:7(2967-2979)Online publication date: 15-Apr-2024

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