3 Factor Authentication Using a Dry-Electrode In-Ear Electroencephalography recorder
A research on the feasibility of several classification methods
P.J. Aanhane (TU Delft - Electrical Engineering, Mathematics and Computer Science)
S.H. Molenkamp (TU Delft - Electrical Engineering, Mathematics and Computer Science)
J.A.J.M. Vrijdag (TU Delft - Electrical Engineering, Mathematics and Computer Science)
Dante G. Muratore – Mentor (TU Delft - Bio-Electronics)
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Abstract
This bachelor end project thesis is describing ways to use dry-electrode electroencephalography (EEG) measurements for authentication. There are five proposed methods based on the literature study, which in this report are called: ’frequency tagging’, ’pseudowords’, ’familiar music’, ’mental tasks’, and ’emotions’. First, all methods were tested, however, this proved too much work to perform each of them thoroughly and wellbounded, so two were selected for further investigation.
For the method involving frequency tagging, experiments were done and the obtained data was used to extract features. This analysis showed that tagging can be discovered in the EEG data, but re-induction of tagged words was hard to achieve, which would make it difficult to create an authentication system reliant on it. Analyzing results from experiments to test the pseudoword method was more promising. Some similarities between the features that were expected from papers and features from our results were found. These features were therefore used for classification, and resulted in small improvements in accuracy. This accuracy did however vary a lot between different data sets.