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

Nick Merrill1, Max T Curran1, Swapan Gandhi2

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Summary
This summary is machine-generated.

Custom in-ear electroencephalography (EEG) earpieces enable discreet brain-computer interfaces (BCIs). This novel system offers high-accuracy, multi-factor authentication without cumbersome head-worn devices.

Keywords:
authenticationbrain-computer interfacehuman-computer interactionin-ear EEGpassthoughtsubiquitous EEGusable security

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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.