Survey of EEG-Based Biometric Authentication

Abstract

Attached

User authentication systems based on EEG (electroencephalography) is currently popular, marking an inflection point in the field. Recently, the scientific community has been making tremendous attempts towards perceiving uniqueness of brain signal patterns. Several types of methodical approaches have been proposed and prototyped to analyze EEG data with various signal-processing methods and pattern-recognition algorithms. Even though there are many stimulation methods to produce reasonable distinctiveness between subjects, optimization and lowering task complexity are still desirable from technoeconomic points of view. With recent technological advancement of EEG signal capturing devices, the process is getting comparatively simpler as devices are capable of providing better portability with reduced calibration time. However, most detailed analysis suggests that a minimal number of most appropriate channels should be selected for better results, even if a system is equipped with the most advanced hardware. Researchers are now focusing on implementing computationally low cost systems with better accuracy, regardless of complexity of the tasks. This paper is a review of several approaches, providing an overview of crucial design considerations in handling EEG data for extended accuracy and practical applicability to authentication