EEG-Based Biometrics: Challenges and Applications
1Universidade de Fortaleza, Fortaleza, Brazil
2Kaunas University of Technology, Kaunas, Lithuania
3University of Porto, Porto, Portugal
4University of Fortaleza, Fortaleza, Brazil
EEG-Based Biometrics: Challenges and Applications
Description
Biometrics is aimed at recognizing individuals based on physical, physiological, or behavioural characteristics of a human body such as fingerprint, gait, voice, iris, and gaze. Currently, the state-of-the art methods for biometric authentication are being incorporated in various access control and personal identity management applications. While the hand-based biometrics (including fingerprint) have been the most often used technology so far, there is growing evidence that electroencephalogram (EEG) signals collected during a perception or mental task can be used for reliable person recognition. However, the domain of EEG-based biometry still faces the problems of improving the accuracy, robustness, security, privacy, and ergonomics of EEG-based biometric systems and substantial efforts are needed towards developing efficient sets of stimuli (visual or auditory) that can be used of person identification in Brain-Computer Interface (BCI) systems and applications.
There are still many challenging problems involved in improving the accuracy, efficiency, and usability of EEG-based biometric systems and problems related to designing, developing, and deploying new security-related BCI applications, for example, for personal authentication on mobile devices, VR (Virtual Reality) headsets, and Internet.
This special issue aims to introduce the recent progress of EEG-based biometrics and addresses the challenges in developing EEG-based biometry systems for various practical applications, while proposing new ideas and directions for future development.
Potential topics include but are not limited to the following:
- EEG biometry
- Data preprocessing, feature extraction, recognition, and matching for EEG-based biometric systems
- Signal processing and machine learning techniques for EEG-based biometrics
- EEG biometric based passwords and encryption
- Cancellable EEG biometrics
- Multimodal (EEG, EMG, ECG, and other biosignals) biometrics
- Pattern recognition for biometrics
- Performance and accuracy evaluation of EEG-based biometric systems
- Protocols, standards, and interfaces for EEG biometrics
- Security and privacy of biometric EEG data
- Information fusion for biometrics involving EEG data
- EEG biometrics for VR applications
- Stimuli sets for EEG-based biometrics
- Passive BCI technology