Abstract
With the embedding of EEG (electro-encephalography) sensors in wireless headsets and other consumer electronics, authenticating users based on their brainwave signals has become a realistic possibility. We undertake an experimental study of the usability and performance of user authentication using consumer-grade EEG sensor technology. By choosing custom tasks and custom acceptance thresholds for each subject, we can achieve 99% authentication accuracy using single-channel EEG signals, which is on par with previous research employing multi-channel EEG signals using clinical-grade devices. In addition to the usability improvement offered by the single-channel dry-contact EEG sensor, we also study the usability of different classes of mental tasks. We find that subjects have little difficulty recalling chosen “pass-thoughts” (e.g., their previously selected song to sing in their mind). They also have different preferences for tasks based on the perceived difficulty and enjoyability of the tasks. These results can inform the design of authentication systems that guide users in choosing tasks that are both usable and secure.
This research was supported in part by the National Science Foundation under award CCF-0424422 (TRUST).
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Chuang, J., Nguyen, H., Wang, C., Johnson, B. (2013). I Think, Therefore I Am: Usability and Security of Authentication Using Brainwaves. In: Adams, A.A., Brenner, M., Smith, M. (eds) Financial Cryptography and Data Security. FC 2013. Lecture Notes in Computer Science, vol 7862. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-41320-9_1
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DOI: https://doi.org/10.1007/978-3-642-41320-9_1
Publisher Name: Springer, Berlin, Heidelberg
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