On the Stability of EEG-based Person Authentication Systems in Different Brain States

  • Nga Tran

    Student thesis: Master's Thesis

    Abstract

    Using EEG signals for person authentication purposes provides distinctive benefits of a new type of
    biometrics that requires the users to be alive when recording, and that are unintrusive, impossible
    to observe or intercept and impossible to mimic. However, EEG signals are known to be sensitive
    to many factors such as user's different emotional states, user's experience toward stimuli, human
    characteristics, health condition and stimulant consumption. In this research, we focus on the stability
    of EEG-based person authentication systems when users are in different brain states, which
    are caused by the aforementioned factors.
    First, a relatively comprehensive investigation on the stability of EEG-based person authentication
    systems is addressed when users are in different brain states, which are caused by mental states
    with two common instances, namely emotional states and experience toward stimuli.
    Secondly, the research further investigates how stable an EEG-based person authentication system
    can produce "EEG passwords" repeatedly when users have different health conditions, different
    stimulant consumption and human characteristics. Based on that, the research finds out which
    EEG patterns related to particular brain states are better for an EEG-based person authentication
    system. Also, it introduces some ideas based on the experimental results, for designing a real-world
    EEG-based person authentication system that is not only stable and highly secure but also comfortable
    for the users.
    Evaluation experiments performed on the benchmark datasets such as DEAP, Australian EEG
    and Alcoholism show that the proposed method is promising.
    Date of Award2021
    Original languageEnglish
    SupervisorShuangzhe Liu (Supervisor) & Dat Tran (Supervisor)

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