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A multi-factor authentication framework relays on the usage of two or more sources of data for identity retrieval. Moving from authors' previous experimentation on two factor biometric authentication frameworks, the present paper shows the impact of the usage of neural networks as a way to fuse the outcomes of the different factors. The aim is to experiment neural networks as a way to map the multidimensional probabilistic space of a multi-factor biometric framework into the mono-dimensional binary space required by an authentication system.
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