2016 IEEE International Conference on Pervasive Computing and Communications (PerCom) (2016)
March 14, 2016 to March 19, 2016
Sugang Li , WINLAB, Rutgers University, North Brunswick, NJ, USA
Ashwin Ashok , Carnegie Mellon University, Pittsburgh, PA, USA
Yanyong Zhang , WINLAB, Rutgers University, North Brunswick, NJ, USA
Chenren Xu , CECA, Peking University, Beijing, China
Janne Lindqvist , WINLAB, Rutgers University, North Brunswick, NJ, USA
Macro Gruteser , WINLAB, Rutgers University, North Brunswick, NJ, USA
In this paper, we present the design, implementation and evaluation of a user authentication system, Headbanger, for smart head-worn devices, through monitoring the user's unique head-movement patterns in response to an external audio stimulus. Compared to today's solutions, which primarily rely on indirect authentication mechanisms via the user's smartphone, thus cumbersome and susceptible to adversary intrusions, the proposed head-movement based authentication provides an accurate, robust, light-weight and convenient solution. Through extensive experimental evaluation with 95 participants, we show that our mechanism can accurately authenticate users with an average true acceptance rate of 95.57% while keeping the average false acceptance rate of 4.43%. We also show that even simple head-movement patterns are robust against imitation attacks. Finally, we demonstrate our authentication algorithm is rather light-weight: the overall processing latency on Google Glass is around 1.9 seconds.
Authentication, Sensors, Time factors, Glass, Robustness, Google, Accelerometers
S. Li, A. Ashok, Y. Zhang, C. Xu, J. Lindqvist and M. Gruteser, "Whose move is it anyway? Authenticating smart wearable devices using unique head movement patterns," 2016 IEEE International Conference on Pervasive Computing and Communications (PerCom)(PERCOM), Sydney, Australia, 2016, pp. 1-9.