MusicID: A Brainwave-Based User Authentication System for Internet of Things

Abstract

We propose MusicID, an authentication solution for smart devices that uses music-induced brainwave patterns as a behavioral biometric modality. We experimentally evaluate MusicID using data collected from real users whilst they are listening to two forms of music: 1) a popular English song and 2) individual's favorite song. We show that an accuracy over 98% for user identification and an accuracy over 97% for user verification can be achieved by using data collected from a 4-electrode commodity brainwave headset. We further show that a single electrode is able to provide an accuracy of approximately 85% and the use of two electrodes provides an accuracy of approximately 95%. As already shown by commodity brain-sensing headsets for meditation applications, we believe, including dry electroencephalogram electrodes in smart headsets are feasible and MusicID has the potential of providing an entry point and continuous authentication framework for upcoming surge of smart devices mainly driven by augmented reality (AR)/virtual reality (VR) applications.