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You Are How You Touch: User Verification on Smartphones via Tapping Behaviors

Published: 21 October 2014 Publication History

Abstract

Smartphone users have their own unique behavioral patterns when tapping on the touch screens. These personal patterns are reflected on the different rhythm, strength, and angle preferences of the applied force. Since smart phones are equipped with various sensors like accelerometer, gyroscope, and touch screen sensors, capturing a user's tapping behaviors can be done seamlessly. Exploiting the combination of four features (acceleration, pressure, size, and time) extracted from smart phone sensors, we propose a non-intrusive user verification mechanism to substantiate whether an authenticating user is the true owner of the smart phone or an impostor who happens to know the pass code. Based on the tapping data collected from over 80 users, we conduct a series of experiments to validate the efficacy of our proposed system. Our experimental results show that our verification system achieves high accuracy with averaged equal error rates of down to 3.65%. As our verification system can be seamlessly integrated with the existing user authentication mechanisms on smart phones, its deployment and usage are transparent to users and do not require any extra hardware support.

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  • (2024)SMARTCOPEPervasive and Mobile Computing10.1016/j.pmcj.2023.10187397:COnline publication date: 1-Jan-2024
  • (2023)Enhanced In-air Signature Verification via Hand Skeleton Tracking to Defeat Robot-level ReplaysProceedings of the 39th Annual Computer Security Applications Conference10.1145/3627106.3627195(451-462)Online publication date: 4-Dec-2023
  • (2023)Smartphone-derived Virtual Keyboard Dynamics Coupled with Accelerometer Data as a Window into Understanding Brain HealthProceedings of the 2023 CHI Conference on Human Factors in Computing Systems10.1145/3544548.3580906(1-15)Online publication date: 19-Apr-2023
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cover image Guide Proceedings
ICNP '14: Proceedings of the 2014 IEEE 22nd International Conference on Network Protocols
October 2014
674 pages
ISBN:9781479962044

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IEEE Computer Society

United States

Publication History

Published: 21 October 2014

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Cited By

View all
  • (2024)SMARTCOPEPervasive and Mobile Computing10.1016/j.pmcj.2023.10187397:COnline publication date: 1-Jan-2024
  • (2023)Enhanced In-air Signature Verification via Hand Skeleton Tracking to Defeat Robot-level ReplaysProceedings of the 39th Annual Computer Security Applications Conference10.1145/3627106.3627195(451-462)Online publication date: 4-Dec-2023
  • (2023)Smartphone-derived Virtual Keyboard Dynamics Coupled with Accelerometer Data as a Window into Understanding Brain HealthProceedings of the 2023 CHI Conference on Human Factors in Computing Systems10.1145/3544548.3580906(1-15)Online publication date: 19-Apr-2023
  • (2023)Swipe gestures for user authentication in smartphonesJournal of Information Security and Applications10.1016/j.jisa.2023.10345074:COnline publication date: 1-May-2023
  • (2022)Touch-behavioral Authentication on Smartphones using Machine LearningCompanion Proceedings of the 27th International Conference on Intelligent User Interfaces10.1145/3490100.3516456(105-108)Online publication date: 22-Mar-2022
  • (2022)Common Evaluation Pitfalls in Touch-Based Authentication SystemsProceedings of the 2022 ACM on Asia Conference on Computer and Communications Security10.1145/3488932.3517388(1049-1063)Online publication date: 30-May-2022
  • (2021)Analyzing the Effectiveness of Touch Keystroke Dynamic Authentication for the Arabic LanguageWireless Communications & Mobile Computing10.1155/2021/99631292021Online publication date: 1-Jan-2021
  • (2021)Multimodal Continuous User Authentication on Mobile Devices via Interaction PatternsWireless Communications & Mobile Computing10.1155/2021/56779782021Online publication date: 1-Jan-2021
  • (2021)Mobile user authentication-Turn it to unlockProceedings of the 2021 6th International Conference on Mathematics and Artificial Intelligence10.1145/3460569.3460577(101-107)Online publication date: 19-Mar-2021
  • (2021)Fine-Grained and Context-Aware Behavioral Biometrics for Pattern Lock on SmartphonesProceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies10.1145/34480805:1(1-30)Online publication date: 30-Mar-2021
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