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EEG-based biometrics for person identification and continuous authentication

EEG-based biometrics for person identification and continuous authentication

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In this chapter, we will provide an overview of EEG biometrics and discuss some of the salient research issues that need to be addressed for making EEG biometric an effective tool for providing information security. We introduce brain signals, especially EEG signals and its analysis methods, before we discuss brainwave biometrics from four aspects, namely the criteria, the elicitation protocols, the feature extraction methods and the classification algorithms. The chapter is then concluded with discussions on how to integrate EEG biometrics with other biometric modalities for continuous authentication, followed by open research questions on the design of EEG-based biometric systems.

Chapter Contents:

  • 13.1 Brain and brainwaves
  • 13.1.1 The human brain
  • 13.1.2 Brain activity recording techniques
  • 13.1.3 EEG sensors and distribution
  • 13.1.4 EEG rhythms and oscillations
  • 13.1.5 EEG analysis
  • 13.2 EEG as biometric identifiers
  • 13.2.1 Criteria
  • 13.2.2 Elicitation of brain response and the protocols
  • 13.2.3 Feature extraction
  • 13.2.4 Classification algorithms
  • 13.3 EEG biometrics for continuous authentication
  • 13.3.1 Authentication systems
  • 13.3.2 Multi-modal biometrics
  • 13.3.3 Fusion schemes
  • 13.3.4 EEG-based multi-modal continuous authentication
  • 13.4 Research directions and challenges
  • References

Inspec keywords: security of data; biometrics (access control); electroencephalography; medical signal processing; feature extraction; signal classification

Other keywords: EEG signals; elicitation protocols; information security; continuous authentication; classification algorithms; EEG-based biometric systems; brain signals; feature extraction methods; brainwave biometrics; person identification

Subjects: Biology and medical computing; Signal processing and detection; Data security; Electrodiagnostics and other electrical measurement techniques; Digital signal processing; Bioelectric signals

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