Review of Authentication Systems based on Electroencephalogram

Authors

  • asmaa Basher Hamza Iraqi Commission for Computer and Informatics
  • rajaa K. Hasoun University of Information Technology and Communications

DOI:

https://doi.org/10.25195/ijci.v50i1.477

Keywords:

eeg, electroencephalogram, authentication

Abstract

Traditional authentication methods, such as the use of passwords and fingerprints, are susceptible to the risks of theft, loss, and forgery. However, an innovative and secure alternative exists in the form of electroencephalogram (EEG)-based authentication systems, which operate by measuring distinctive brainwave patterns. This particular review undertakes a comprehensive analysis of the current state of EEG-based authentication, delving into its advantages, challenges, and potential future directions. In doing so, we examine the underlying principles governing the acquisition and processing of EEG signals, explore the various techniques employed for feature extraction and classification, and evaluate the performance of existing systems. Moreover, we emphasize the significant advantages offered by EEG-based authentication, including its exceptional accuracy, capacity for liveness detection, and robust resistance to spoofing attempts. Nevertheless, we must also acknowledge and address the various obstacles that must be overcome to facilitate wider adoption of this authentication method, encompassing concerns relating to hardware affordability, user acceptance, and data privacy. Finally, we outline a series of promising research avenues that can potentially address these challenges and unlock the complete potential of EEG-based authentication, thereby enabling secure and convenient access control across a diverse range of domains.

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Author Biographies

asmaa Basher Hamza, Iraqi Commission for Computer and Informatics

Informatics Institute for Postgraduate

rajaa K. Hasoun, University of Information Technology and Communications

Department of Information System Management

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Published

2024-06-30