Researchers developing brainwave biometric system leveraging “chill response” to music
California State Polytechnic University researchers have developed a biometric authentication system based on the decoding of brainwave patterns by a device they call an electroencephalogram (EEG) Workbench.
In an interview with PCMag, Cal Poly Associate Professor Dr. Mohammad I. Hussain and undergraduate Joseph Cauthen describe the technology as addressing the problem of how to prevent a credential breach, whether of password or biometric data, from exposing the system it is supposed to protect. Hussain refers to the mental state in which the brainwave signature is captured for authentication as the “Chill Response.”
The “Chill Response” is induced by playing certain music, which makes the system safe from forced entry under duress. The user must have the same brainwave pattern, and therefore must be relaxed and in the presence of the same stimulus (the music) for authentication to work.
EEG signals are captured from a brain-machine interface as music plays for 30 seconds, and the data is ported into the EEG Workbench, which was developed by Luis Gutierrez as part of his Masters thesis. The system must be trained through repeated examples to recognize the user, and the researchers describe the work as being in early stages.
The main challenges they face are the lack of available data to train the machine learning system, and the limited availability of brain-machine interfaces. The system has been developed for Android, due to the Neurosky SDK and lack of cost for development tools compared to iOS.
Scientists at the University of Buffalo have developed a system for a biometric “brain password” by measuring EEG responses to a series of pictures.