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Review on EEG-Based Authentication Technology.

Shuai Zhang1, Lei Sun1, Xiuqing Mao1

  • 1Information Engineering University, Zhengzhou 450001, China.

Computational Intelligence and Neuroscience
|January 3, 2022
PubMed
Summary
This summary is machine-generated.

Electroencephalogram (EEG) signals offer a novel biometric solution for secure brain-computer interfaces. EEG-based biometric cryptosystems enhance authentication security and introduce revocability, addressing limitations of traditional methods.

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Area of Science:

  • Biometrics
  • Neuroscience
  • Computer Science

Background:

  • Brain-computer interface (BCI) technology is rapidly advancing.
  • Electroencephalogram (EEG) signals are emerging as a novel biometric feature.
  • Traditional biometric authentication faces long-term security challenges.

Purpose of the Study:

  • To review the biometrics of EEG signals for authentication.
  • To introduce EEG-based biometric cryptosystems.
  • To analyze the latest research in EEG-based authentication.

Main Methods:

  • Systematic review of EEG signal biometrics.
  • Analysis of cryptographic techniques applied to EEG authentication.
  • Introduction of EEG-based biometric cryptosystems.

Main Results:

  • EEG signals provide a viable biometric feature for authentication.
  • EEG-based biometric cryptosystems enhance security and protect biometric data.
  • These systems offer revocability, an advantage over traditional biometrics.

Conclusions:

  • EEG-based authentication presents a promising solution for BCI security.
  • Further research is needed to address existing challenges and future directions.
  • This review provides a reference for identity authentication technology based on EEG signals.