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 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.

[1]  Yan Wang,et al.  Friend or Foe?: Your Wearable Devices Reveal Your Personal PIN , 2016, AsiaCCS.

[2]  Wan-Young Chung,et al.  Standalone Wearable Driver Drowsiness Detection System in a Smartwatch , 2016, IEEE Sensors Journal.

[3]  Parth H. Pathak,et al.  Finger-writing with Smartwatch: A Case for Finger and Hand Gesture Recognition using Smartwatch , 2015, HotMobile.

[4]  Xiaohui Liang,et al.  AuthoRing: Wearable User-presence Authentication , 2017, WearSys@MobiSys.

[5]  Yangsheng Xu,et al.  Support Vector Machine for Behavior-Based Driver Identification System , 2010, J. Robotics.

[6]  Sadaoki Furui,et al.  Speaker-independent isolated word recognition using dynamic features of speech spectrum , 1986, IEEE Trans. Acoust. Speech Signal Process..

[7]  Claudia Picardi,et al.  User authentication through keystroke dynamics , 2002, TSEC.

[8]  Ahmed Awad E. Ahmed,et al.  A New Biometric Technology Based on Mouse Dynamics , 2007, IEEE Transactions on Dependable and Secure Computing.

[9]  Wan-Young Chung,et al.  Wristband-Type Driver Vigilance Monitoring System Using Smartwatch , 2015, IEEE Sensors Journal.

[10]  Adrian Popescu,et al.  Multimodal feature generation framework for semantic image classification , 2012, ICMR.

[11]  Chih-Jen Lin,et al.  LIBSVM: A library for support vector machines , 2011, TIST.

[12]  Deron Liang,et al.  A novel driver identification method using wearables , 2016, 2016 13th IEEE Annual Consumer Communications & Networking Conference (CCNC).

[13]  Kazuya Takeda,et al.  Driver Modeling Based on Driving Behavior and Its Evaluation in Driver Identification , 2007, Proceedings of the IEEE.

[14]  Xiangping Sun,et al.  Driver Recognition Based on Dynamic Handgrip Pattern on Steeling Wheel , 2011, 2011 12th ACIS International Conference on Software Engineering, Artificial Intelligence, Networking and Parallel/Distributed Computing.

[15]  Xiangyu Liu,et al.  When Good Becomes Evil: Keystroke Inference with Smartwatch , 2015, CCS.

[16]  Chien-Feng Huang,et al.  利用高斯混合模型及支持向量機之 駕駛者生物特徵驗證研究;Driver Verification based on Biometric using GMM and SVM , 2016 .

[17]  Mengjun Xie,et al.  Real time motion-based authentication for smartwatch , 2016, 2016 IEEE Conference on Communications and Network Security (CNS).

[18]  Martin Tomitsch,et al.  Energy-Efficient Integration of Continuous Context Sensing and Prediction into Smartwatches , 2015, Sensors.

[19]  Dino Isa,et al.  Feature Selection Based on Minimizing the Area Under the Detection Error Tradeoff Curve , 2011, Int. J. Appl. Evol. Comput..

[20]  Stéphane Ayache,et al.  Classifier Fusion for SVM-Based Multimedia Semantic Indexing , 2007, ECIR.

[21]  Kirsi Helkala,et al.  Biometric Gait Authentication Using Accelerometer Sensor , 2006, J. Comput..

[22]  Douglas A. Reynolds,et al.  A Tutorial on Text-Independent Speaker Verification , 2004, EURASIP J. Adv. Signal Process..

[23]  Blaine A. Price,et al.  Wearables: has the age of smartwatches finally arrived? , 2015, Commun. ACM.

[24]  Lina Yao,et al.  Fall Detection Using Smartwatch Sensor Data with Accessor Architecture , 2017, ICSH.

[25]  Alvin F. Martin,et al.  The DET curve in assessment of detection task performance , 1997, EUROSPEECH.

[26]  Tieniu Tan,et al.  Fusion of static and dynamic body biometrics for gait recognition , 2003, IEEE Transactions on Circuits and Systems for Video Technology.

[27]  Hiok Chai Quek,et al.  Driving Profile Modeling and Recognition Based on Soft Computing Approach , 2009, IEEE Transactions on Neural Networks.

[28]  Anne H. H. Ngu,et al.  Real-Time Prediction of Blood Alcohol Content Using Smartwatch Sensor Data , 2015, ICSH.

[29]  Agnes Grünerbl,et al.  Smart-watch life saver: smart-watch interactive-feedback system for improving bystander CPR , 2015, SEMWEB.

[30]  Majid Sarrafzadeh,et al.  Audio-based detection and evaluation of eating behavior using the smartwatch platform , 2015, Comput. Biol. Medicine.

[31]  Deron Liang,et al.  A Novel Non-intrusive User Authentication Method Based on Touchscreen of Smartphones , 2013, 2013 International Symposium on Biometrics and Security Technologies.

[32]  David H. Wolpert,et al.  Stacked generalization , 1992, Neural Networks.

[33]  Hüseyin Abut,et al.  Biometric identification using driving behavioral signals , 2004, 2004 IEEE International Conference on Multimedia and Expo (ICME) (IEEE Cat. No.04TH8763).

[34]  Alois Ferscha,et al.  Supporting Implicit Human-to-Vehicle Interaction: Driver Identification from Sitting Postures , 2008 .