Using brain waves as transparent biometrics for on-demand driver authentication

Conventional biometric systems mainly assume one-time-only authentication. However, this technique is not used with user management applications. If a user is replaced by an imposter after the authentication has occurred, the systems cannot detect such a replacement. One solution to this problem is on-demand authentication, in which users are authenticated on a regular or non-regular schedule, as determined by the system. However, the on demand-authentication technique requires that we present biometric data without regard to do so. In this paper, we focus on the use of brain waves as transparent biometric signals. In particular, we assume driver authentication and measure the brain waves of drivers when they are performing mental tasks such as tracing routes or using a simplified driving simulator as an actual task. We propose to extract the power spectrum in the α–β band as an individual feature and propose two verification methods based on the similarity of the features. In addition, we propose to divide the α–β band into either four or six partitions and to fuse the similarity scores from all the partitions. We evaluate the verification performance using 23 subjects and obtain an equal error rate of 20–25%.