Abstract
Recently, electroencephalography (EEG) is considered as a new potential type of user authentication with many security advantages of being difficult to fake, impossible to observe or intercept, unique, and alive person recording require. The difficulty is that EEG signals are very weak and subject to the contamination from many artifact signals. However, for the applications in human health, true EEG signals, without the contamination, is highly desirable, but for the purposes of authentication, where stable and repeatable patterns from the source signals are critical, the origins of the signals are of less concern. In this paper, we propose an EEG-based authentication method, which is simple to implement and easy to use, by taking the advantage of EEG artifacts, generated by a number of purposely designed voluntary facial muscle movements. These tasks can be single or combined, depending on the level of security required. Our experiment showed that using EEG artifacts for user authentication in multilevel security systems is promising.
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Pham, T., Ma, W., Tran, D., Nguyen, P., Phung, D. (2014). EEG-Based User Authentication Using Artifacts. In: de la Puerta, J., et al. International Joint Conference SOCO’14-CISIS’14-ICEUTE’14. Advances in Intelligent Systems and Computing, vol 299. Springer, Cham. https://doi.org/10.1007/978-3-319-07995-0_34
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DOI: https://doi.org/10.1007/978-3-319-07995-0_34
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-07994-3
Online ISBN: 978-3-319-07995-0
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