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International Journal of Cognitive Biometrics

 

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International Journal of Cognitive Biometrics (2 papers in press)

 

Regular Issues

 

  • PIN Generation Using EEG: A Stability Study   Order a copy of this article
    by Ramaswamy Palaniappan, Kenneth Revett 
    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 the method is obviously its 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.
    Keywords: Biometrics; Brian-computer Interface; Electroencephalogram; Personal Identification Number; Neural Networks
     
  • Biometric verification of a user based on eye movements   Order a copy of this article
    by Youming Zhang, Martti Juhola 
    Abstract: The biometric verification of users of computers or other machines is usually performed with fingerprints, face images or even iris or palm images. Eye movements have seldom been studied for biometric verification, although in the future their use will perhaps extend from laboratory applications to integrated parts of computer interfaces. Eye movements have long been studied in medical and psychological applications. We have noticed that there are differences between saccade eye movements of individuals, even in a group of young people approximately of the same age. We measured saccades from 68 voluntary subjects by performing the same stimulation for each to obtain comparable data. We tested two verification conditions: (1) an authenticated user vs. all other subjects and (2) an impostor vs. an authenticated user and others. Thorough randomized classifications with discriminant analysis, k-d tree and k nearest-neighbour searching, decision trees and the na
    Keywords: Eye movements; saccade; user verification; signal analysis; classification