Biometric authentication systems are currently highly demanded, yet they are facing efficiency and accessibility challenges in terms of te unimodality. This paper addresses those problems and proposes a multimodal biometric system as a solution. The system includes two biometric models: Electroencephalography (EEG) and face recognition. In addition, the proposed multimodal biometric system includes a non-biometric model, known as SMS token. The work presented in this paper describes the feature extraction from the cloud storage of the biometric data and the best multimodal fusion technique for model combination.
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