MusicID: A Brainwave-based User Authentication System for Internet of Things
This provides a novel authentication method for smart devices, particularly in AR/VR contexts, though it is incremental as it builds on existing brain-sensing technology.
The authors tackled user authentication for IoT devices by developing MusicID, a system that uses music-induced brainwave patterns as a behavioral biometric, achieving over 98% accuracy for user identification and over 97% for verification with a 4-electrode headset.
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; a popular English song and 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 EEG electrodes in smart-headsets is 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.