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

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 Award	2021
Original language	English
Supervisor	Shuangzhe LIU (Supervisor) & Dat Tran (Supervisor)