One-Step, Three-Factor Passthought Authentication With Custom-Fit, In-Ear EEG.

Area of Science:

• Biomedical Engineering
• Neuroscience
• Human-Computer Interaction

Background:

• In-ear electroencephalography (EEG) presents a novel modality for discreet brain-computer interfaces (BCIs).
• Existing BCI systems often rely on cumbersome head-worn devices, limiting usability.
• Developing secure and user-friendly authentication methods is crucial for BCI adoption.

Purpose of the Study:

• To develop and evaluate a brain-based authentication system utilizing custom-fit in-ear EEG earpieces.
• To assess the accuracy and robustness of the in-ear EEG authentication system.
• To demonstrate the potential of in-ear EEG for secure and usable authentication.

Main Methods:

• Custom-fit in-ear EEG earpieces were designed and fabricated.
• A brain-based authentication system was implemented using the in-ear EEG data.
• Participant authentication accuracy was evaluated, including inherence and knowledge factors.
• A simulated impersonation attack was conducted to test system robustness.

Main Results:

• The custom-fit in-ear EEG system achieved high authentication accuracy, surpassing previous non-custom earpiece studies.
• Both physiological (inherence) and cognitive (knowledge) factors contributed significantly to authentication.
• The system demonstrated robustness against simulated impersonation attacks.
• The in-ear design eliminated the need for cumbersome head-worn equipment.

Conclusions:

• Custom-fit in-ear EEG earpieces provide a viable and accurate solution for discreet brain-computer interfaces.
• This system offers a unique, multi-factor authentication method integrated into a single, user-friendly device.
• In-ear EEG technology holds significant promise for enhancing BCI usability and security for diverse user populations.