Verification of fraudulent PIN holders by brain waves

Hiromichi Iwasa, Teruki Horie, Yasuo Matsuyama

    Research output: Chapter in Book/Report/Conference proceedingConference contribution


    are applicable to user verification. We devise a two-factor system so that impersonators who hold identification numbers in fraudulence are detectable. In the first step, a subject either authentic or false tries to input a digit of a ten-key in the personal identification number by a P300 speller. The P300 speller is a brain-computer interface that detects positive voltage jump when a subject identifies specific digits on a display visually. By considering the performance of the P300 speller, we allow an error of one digit out of the four digits. On the other hand, we keep suspicion even for the case of perfect four digits because of the possibility of impersonation by a stolen case. Following the P300 spelling, we apply a verification of subjects by brain waves. Averaging of detected P300 waveforms after band-pass filtering takes the role of feature extraction. Then, a support vector machine applied to the averaged waveforms decides whether the subject is authentic or false. Thus, the total system does not entail the complexity of multimodality. For this system, we measured average error rates for 20 subjects. Experiments showed the false rejection rate of 3.9% at the false acceptance rate of 0% for the 4-digit number case. These pair values are successfully low even by using brain waves that usually contain many artifacts. Additionally, experiments on a diabetes patient before and after an insulin injection are also conducted. The result shows that the appropriate injection control maintains no difference from ordinary subjects. In concluding remarks, we consider methods to increase subjects and digits for applications in a larger society.

    Original languageEnglish
    Title of host publication2016 International Joint Conference on Neural Networks, IJCNN 2016
    PublisherInstitute of Electrical and Electronics Engineers Inc.
    Number of pages8
    ISBN (Electronic)9781509006199
    Publication statusPublished - 2016 Oct 31
    Event2016 International Joint Conference on Neural Networks, IJCNN 2016 - Vancouver, Canada
    Duration: 2016 Jul 242016 Jul 29


    Other2016 International Joint Conference on Neural Networks, IJCNN 2016


    • EEG
    • P300 speller
    • PIN
    • Two-factor authentication
    • Verification

    ASJC Scopus subject areas

    • Software
    • Artificial Intelligence


    Dive into the research topics of 'Verification of fraudulent PIN holders by brain waves'. Together they form a unique fingerprint.

    Cite this