• DocumentCode
    722543
  • Title

    A new non-intrusive authentication method based on dynamics of driver´s upper body joint angles

  • Author

    Ching-Han Yang ; Deron Liang ; Chin-Chun Chang ; Chien-Cheng Lin

  • Author_Institution
    Dept. of Comput. Sci. & Inf. Eng., Nat. Central Univ., Taoyuan, Taiwan
  • fYear
    2015
  • fDate
    9-12 Jan. 2015
  • Firstpage
    341
  • Lastpage
    346
  • Abstract
    Today, vehicles have been an essential part of our daily life. Existing vehicle security systems rely primarily on lock devices, alarm systems or fingerprints as forms of protection. A non-intrusive driver authentication mechanism could be incorporated into existing vehicle security system to offer a greater degree of multilevel protection. In this paper, we propose a novel non-intrusive authentication mechanism based on dynamics of driver´s upper body joint angles. This new approach is based on the hypothesis that a driver has a specific habit to drive a vehicle; and such behavioral biometrics can be captured from the motion capture system. We design an authentication mechanism that adopted 40 new features transformed from the information of the driver´s upper body joints. To validate this hypothesis, we have used iPi motion capture system to collect driver´s behavioral biometrics. The experimental results show that the proposed approach has an equal error rate about 13%.
  • Keywords
    biometrics (access control); driver information systems; image capture; image motion analysis; intelligent transportation systems; message authentication; pose estimation; behavioral biometrics; driver upper body joint angle dynamics; iPi motion capture system; intelligent system; multilevel protection; nonintrusive driver authentication mechanism; vehicle security system; Authentication; Biometrics (access control); Elbow; Joints; Shoulder; Vehicles; Biometrics; Driving Behavior; Upper Body Joint Angle; User Authentication;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Consumer Communications and Networking Conference (CCNC), 2015 12th Annual IEEE
  • Conference_Location
    Las Vegas, NV
  • ISSN
    2331-9860
  • Print_ISBN
    978-1-4799-6389-8
  • Type

    conf

  • DOI
    10.1109/CCNC.2015.7157999
  • Filename
    7157999