A Novel GMM-Based Behavioral Modeling Approach for Smartwatch-Based Driver Authentication
All drivers have their own distinct driving habits, and usually hold and operate the steering wheel differently in different driving scenarios. In this study, we proposed a novel Gaussian mixture model (GMM)-based method that can improve the traditional GMM in modeling driving behavior. This new met...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
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MDPI AG
2018-03-01
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| Series: | Sensors |
| Subjects: | |
| Online Access: | http://www.mdpi.com/1424-8220/18/4/1007 |
| _version_ | 1811262775470587904 |
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| author | Ching-Han Yang Chin-Chun Chang Deron Liang |
| author_facet | Ching-Han Yang Chin-Chun Chang Deron Liang |
| author_sort | Ching-Han Yang |
| collection | DOAJ |
| description | All drivers have their own distinct driving habits, and usually hold and operate the steering wheel differently in different driving scenarios. In this study, we proposed a novel Gaussian mixture model (GMM)-based method that can improve the traditional GMM in modeling driving behavior. This new method can be applied to build a better driver authentication system based on the accelerometer and orientation sensor of a smartwatch. To demonstrate the feasibility of the proposed method, we created an experimental system that analyzes driving behavior using the built-in sensors of a smartwatch. The experimental results for driver authentication—an equal error rate (EER) of 4.62% in the simulated environment and an EER of 7.86% in the real-traffic environment—confirm the feasibility of this approach. |
| first_indexed | 2024-04-12T19:32:47Z |
| format | Article |
| id | doaj.art-25c2167c050b4de2b4b4f0e13c774f08 |
| institution | Directory Open Access Journal |
| issn | 1424-8220 |
| language | English |
| last_indexed | 2024-04-12T19:32:47Z |
| publishDate | 2018-03-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Sensors |
| spelling | doaj.art-25c2167c050b4de2b4b4f0e13c774f082022-12-22T03:19:18ZengMDPI AGSensors1424-82202018-03-01184100710.3390/s18041007s18041007A Novel GMM-Based Behavioral Modeling Approach for Smartwatch-Based Driver AuthenticationChing-Han Yang0Chin-Chun Chang1Deron Liang2Department of Computer Science and Information Engineering, National Central University, Taoyuan City 32001, Taiwan, <email>drliang@csie.ncu.edu.tw</email>Department of Computer Science and Engineering, National Taiwan Ocean University, Keelung City 20224, Taiwan, <email>cvml@mail.ntou.edu.tw</email>Department of Computer Science and Information Engineering, National Central University, Taoyuan City 32001, Taiwan, <email>drliang@csie.ncu.edu.tw</email>All drivers have their own distinct driving habits, and usually hold and operate the steering wheel differently in different driving scenarios. In this study, we proposed a novel Gaussian mixture model (GMM)-based method that can improve the traditional GMM in modeling driving behavior. This new method can be applied to build a better driver authentication system based on the accelerometer and orientation sensor of a smartwatch. To demonstrate the feasibility of the proposed method, we created an experimental system that analyzes driving behavior using the built-in sensors of a smartwatch. The experimental results for driver authentication—an equal error rate (EER) of 4.62% in the simulated environment and an EER of 7.86% in the real-traffic environment—confirm the feasibility of this approach.http://www.mdpi.com/1424-8220/18/4/1007accelerometer sensordriver authenticationGaussian mixture modelsorientation sensorsmartwatch |
| spellingShingle | Ching-Han Yang Chin-Chun Chang Deron Liang A Novel GMM-Based Behavioral Modeling Approach for Smartwatch-Based Driver Authentication Sensors accelerometer sensor driver authentication Gaussian mixture models orientation sensor smartwatch |
| title | A Novel GMM-Based Behavioral Modeling Approach for Smartwatch-Based Driver Authentication |
| title_full | A Novel GMM-Based Behavioral Modeling Approach for Smartwatch-Based Driver Authentication |
| title_fullStr | A Novel GMM-Based Behavioral Modeling Approach for Smartwatch-Based Driver Authentication |
| title_full_unstemmed | A Novel GMM-Based Behavioral Modeling Approach for Smartwatch-Based Driver Authentication |
| title_short | A Novel GMM-Based Behavioral Modeling Approach for Smartwatch-Based Driver Authentication |
| title_sort | novel gmm based behavioral modeling approach for smartwatch based driver authentication |
| topic | accelerometer sensor driver authentication Gaussian mixture models orientation sensor smartwatch |
| url | http://www.mdpi.com/1424-8220/18/4/1007 |
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