Driver Authentication for Smart Car Using Wireless Sensing

In the present evolving world, automobiles have become an intelligent electronic machine and are no longer a mere transport medium. In this article, we attempt to make them smarter by introducing the idea of in-car driver authentication using wireless sensing and develop a system that can recognize drivers automatically. The proposed system can recognize human identity by identifying the unique radio biometric information recorded in the channel state information (CSI) through multipath propagation. However, since the environmental information is also captured in the CSI, the performance of radio biometric recognition may be degraded by the changing environment. In this article, we first address the problem of “in-car changing environments” where the existing wireless sensing-based human identification system fails. We build a long-term driver radio biometric database consisting of radio biometrics of seven people collected over a period of two months. We leverage this database to create machine learning models that make the proposed system adaptive to new in-car environments. Second, we study the performance of the in-car driver authentication system with increasing effective bandwidth. We realize an effective bandwidth of 960 MHz by exploiting the multiantenna and frequency diversities in commercial WiFi devices. The performance of the proposed system is shown to improve with increasing effective bandwidth and the long-term experiments demonstrate the feasibility and accuracy of the proposed system. The accuracy achieved in the two-driver scenario is up to 99.13% for the best case.