ReviewInternational journal of telemedicine and applications2025
Threats and Mitigation Strategies for Electroencephalography-Based Person Authentication.
Review in International journal of telemedicine and applications, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
What it found
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Who cites it
6 citing papers in PubMed.
- Data-Efficient EEG-Based Person Identification via Time-Interval-Based Multi-Positive Contrastive Learning.Sensors (Basel, Switzerland) · 2026Article
- EEG Subject Identification and Open-Set Rejection Across Paradigms.Sensors (Basel, Switzerland) · 2026Article
- Disentangling EEG Fingerprinting and Sleep Biomarkers Using Generalized Weighted Ordinal Patterns.Brain sciences · 2026Article
- EEG-based harmful brain activity classification using deep learning and feature fusion.Scientific reports · 2026Article
- Mapping EEG Metrics to Human Affective and Cognitive Models: An Interdisciplinary Scoping Review from a Cognitive Neuroscience Perspective.Biomimetics (Basel, Switzerland) · 2025Review
- Evaluation of entropy features and classifier performance in person authentication using resting-state EEG.Frontiers in neuroscience · 2025Article
Corrections and comments
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Authors and funding
7 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
This work is aimed at investigating the potential risks linked to electroencephalography (EEG)-based person authentication and providing solutions to mitigate these issues. Authenticating a person by EEG involves verifying the legitimacy of the signals used for user identification. EEG signals serve as a biometric modality for authentication and verification. Additional biometric modalities, such as fingerprints or irises, are vulnerable to both fabrication and degradation over time, and illicit use of dead people's biometrics has sometimes been seen. EEG's intrinsic properties prohibit signal imitation or postmortem acquisition, making it more reliable than other biometric modalities. This research is aimed at investigating the most recent advancements in the domain of EEG signals, clarifying the current knowledge that impacts EEG-based authentication, and evaluating the emerging challenges. Many research publications have been collected to achieve this objective. By considering historical and recent efforts and achievements, this research also presents feasible resolutions to the emerging inquiries prompted by the ongoing advancements in EEG-based technology. The potential future application of EEG-based authentication has also been the subject of this scholarly discourse. A comprehensive collection of articles over the previous decade has been compiled to answer contemporary EEG signal research questions to get valuable insights. According to research findings, in February 2022, a significant milestone was achieved when the EEG signals of a deceased person were successfully captured for the first time in recorded history. However, this groundbreaking discovery may threaten EEG-based authentication. In addition, it is found that EEG-based authentication literature did not completely implement "liveness detection." An updated approach for identifying liveness addresses novel challenges, that is, falsified EEG signals and a dead person's EEG signals for EEG-based authentication that have not been discussed in the literature. The suggested solutions put forward in this study have the potential to stimulate additional research in this area.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.