Systematic Review of Brain-Computer Interface-Based User Authentication System: Trends, Challenges, and Directions

Abstract

The authentication process plays a crucial role in ensuring accurate and high-level security in various applications, particularly in the face of emerging technologies and the growing threat of unauthorized access. Through a comprehensive review of previous studies on brain-computer interface (BCI)-based authentication, we have identified it as a secure and promising solution, harnessing the unique characteristics of brainwaves. The main objective of this research is to systematically categorized the literature based on modality, authentication type, BCI paradigm, stimuli and signals types, computational and machine learning methods, databases, and BCI devices. We used the preferred reporting items for systematic reviews and meta-analyses (PRISMA2020) model in conducting this review. We extracted detailed information from previous studies to gain a deeper understanding of the advancements, challenges, potential applications BCI-based authentication systems. We classified the challenges encountered by BCI systems into three categories: technological, user related, and implementation and suggested the future research directions for each of them. In this study, we presented a systematic literature review the field of BCI-based authentication to provide researchers and practitioners with a comprehensive overview of the advancements, trends, challenges, and future directions in this area.

Keywords

• Brain–computer interfaces
• authentication
• identification
• machine learning
• signal processing