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Abstract
With 2-factor authentication practices becoming ever more popular, the need for developing new authentication procedures is gaining ever more traction. Rhythm-based gesture authentication appears to be a promising area of research as it encompasses two of the three main authenticator factors: something you know(the chosen rhythm) and something you are(how you enter that rhythm). Rhythm-based authentication approaches have mostly been achieved using touchscreen functions. But accelerometers and gyroscope sensors have the unique ability to capture the small differences in how users enter a set rhythm and how they hold their phone. Additionally, these sensors do not limit our approach to mobile devices with mobile screens but can be expanded to headsets, smart glasses, and screen-less fitness trackers. It also circumvents issues like wearing face masks and gloves. All 12 of our participants were asked to input the same tapping rhythm consisting of 7 taps, 50 times, totaling 600 samples to be used for trial and testing. If our system is able to perform well under these conditions it proves that even an attacker who knows your rhythm, wouldn't be able to access your device. This could be equated to you telling someone your password, but them still not being able to gain access to your phone. Our models were able to achieve an authentication accuracy of 99.65% only using 10 valid samples for training and an identification accuracy of 99.17 %. © 2023 IEEE.
| Original language | English |
|---|---|
| Title of host publication | IECON 2023- 49th Annual Conference of the IEEE Industrial Electronics Society |
| Publisher | IEEE |
| ISBN (Electronic) | 979-8-3503-3182-0 |
| ISBN (Print) | 979-8-3503-3183-7 |
| DOIs | |
| Publication status | Published - 2023 |
| Event | 49th Annual Conference of the IEEE Industrial Electronics Society (IECON 2023) - Marina Bay Sands Expo and Convention Centre, Singapore Duration: 16 Oct 2023 → 19 Oct 2023 https://www.iecon2023.org/ |
Publication series
| Name | IECON Proceedings (Industrial Electronics Conference) |
|---|---|
| ISSN (Print) | 1553-572X |
| ISSN (Electronic) | 2577-1647 |
Conference
| Conference | 49th Annual Conference of the IEEE Industrial Electronics Society (IECON 2023) |
|---|---|
| Abbreviated title | IEEE IECON 2023 |
| Place | Singapore |
| Period | 16/10/23 → 19/10/23 |
| Internet address |
Funding
This work was supported by the Research Grants Council of Hong Kong under project CityU 1121462
Research Keywords
- Behavioral Biometrics
- Gesture Authentication
- Smart Wearable Device
Publisher's Copyright Statement
- COPYRIGHT TERMS OF DEPOSITED POSTPRINT FILE: © 2023 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works. Boshoff, D., Nkrow, R., & Hancke, G. P. (2023). Knock-to-Enter Authentication: A Rhythm-Based Smartphone Authentication Mechanism. In IECON 2023- 49th Annual Conference of the IEEE Industrial Electronics Society (IECON Proceedings (Industrial Electronics Conference)). IEEE. https://doi.org/10.1109/IECON51785.2023.10312590
RGC Funding Information
- RGC-funded
Fingerprint
Dive into the research topics of 'Knock-to-Enter Authentication: A Rhythm-Based Smartphone Authentication Mechanism'. Together they form a unique fingerprint.Projects
- 1 Finished
-
GRF: Error-Correcting Response Functions for Distance-Bounding Protocols
HANCKE, G. P. (Principal Investigator / Project Coordinator) & Liu, Z. (Co-Investigator)
1/01/21 → 24/06/25
Project: Research
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