PIN generation using EEG: a stability study. (1st January 2014)

• Record Type: Journal Article
• Authors: Palaniappan, Ramaswamy; Revett, Kenneth
• Is Part Of: International journal of biometrics. Volume 6:Number 2(2014)
• Page Start: 95
• Page End: 105
• Publication Date: 2014-01-01
• Subjects: biometrics -- BCI -- brain–computer interface -- EEG -- electroencephalogram -- personal identification number -- neural networks; Biometric identification -- Periodicals; Biometry -- Periodicals; 570.15195
• Languages: English
• ISSNs: 1755-8301

Abstract

In a previous study, it has been shown that brain activity, i.e., electroencephalogram (EEG) signals, can be used to generate personal identification number (PIN). The method was based on brain-computer interface (BCI) technology using a P300-based BCI approach and showed that a single-channel EEG was sufficient to generate PIN without any error for three subjects. The advantage of this method is obviously its better fraud resistance compared to conventional methods of PIN generation such as entering the numbers using a keypad. Here, we investigate the stability of these EEG signals when used with a neural network classifier, i.e., to investigate the changes in the performance of the method over time. Our results, based on recording conducted over a period of three months, indicate that a single channel is no longer sufficient and a multiple electrode configuration is necessary to maintain acceptable performances. Alternatively, a recording session to retrain the neural network classifier can be conducted on shorter intervals, though practically this might not be viable.