Personalizable neurological user authentication framework

Brain Computer Interfaces (BCIs) stand as a promising new technology to enrich interaction with objects in both the physical and virtual world. As BCI technology continues to mature for possibly becoming a essential part of the future communication and interaction with people and objects, more attention is needed for effectively and accurately authenticating the very user of the input device. We attempt to analyze and improve current and new methods of user authentication that can be provided through consumer-grade BCIs. We first propose a new neurological framework for an authentication system integrated with BCIs. We then evaluate the effectiveness of the framework in conjunction with the fidelity and usability of electroencephalogram (EEG) data obtained from a consumer-grade BCI to analyze different types of sensory pass-thoughts and their effectiveness among individuals. Preliminary results show that the proposed framework is promising to improve the accuracy of neurological user authentication.