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Mobile user authentication-Turn it to unlock

Published: 31 August 2021 Publication History

Abstract

Nowadays, with the prosperous development of smartphone, abundant applications in smartphone have sprung up. To secure privacy information of users from being leaked, user authentication become necessary and important. Traditional authentication scheme such as password are vulnerable to shoulder surfing attacks and smudge attacks. Physiological biometric authentication schemes usually have some limitations when people using. More importantly, once the physiological information leaked will cause serious consequences. In contrast, behavioral biometric authentication schemes are secure and convenient. In this paper, we propose a handy user authentication scheme by simply turning over the phone. The scheme uses embedded motion sensors to effectively capture the unique user behavior. We recruited 19 volunteers with about 760,000 turning samples collected over multiple weeks under sitting and standing postures. Eventually, the scheme we proposed is available to use and deploy in smartphone.

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Cited By

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  • (2024)The utility of behavioral biometrics in user authentication and demographic characteristic detection: a scoping reviewSystematic Reviews10.1186/s13643-024-02451-113:1Online publication date: 8-Feb-2024
  • (2023)Deep Learning and Machine Learning, Better Together Than Apart: A Review on Biometrics Mobile AuthenticationJournal of Cybersecurity and Privacy10.3390/jcp30200133:2(227-258)Online publication date: 13-Jun-2023
  • (2022)PushPIN: A Pressure-Based Behavioral Biometric Authentication System for SmartwatchesInternational Journal of Human–Computer Interaction10.1080/10447318.2022.204914439:4(893-909)Online publication date: 19-Apr-2022

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cover image ACM Other conferences
ICMAI '21: Proceedings of the 2021 6th International Conference on Mathematics and Artificial Intelligence
March 2021
142 pages
ISBN:9781450389464
DOI:10.1145/3460569
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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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 31 August 2021

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Author Tags

  1. Behavioral biometrics
  2. Inertial sensors
  3. Key words: User authentication
  4. Smartphone

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Cited By

View all
  • (2024)The utility of behavioral biometrics in user authentication and demographic characteristic detection: a scoping reviewSystematic Reviews10.1186/s13643-024-02451-113:1Online publication date: 8-Feb-2024
  • (2023)Deep Learning and Machine Learning, Better Together Than Apart: A Review on Biometrics Mobile AuthenticationJournal of Cybersecurity and Privacy10.3390/jcp30200133:2(227-258)Online publication date: 13-Jun-2023
  • (2022)PushPIN: A Pressure-Based Behavioral Biometric Authentication System for SmartwatchesInternational Journal of Human–Computer Interaction10.1080/10447318.2022.204914439:4(893-909)Online publication date: 19-Apr-2022

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