Biometric-Based Key Generation and User Authentication Using Voice Password Images and Neural Fuzzy Extractor
Alexey Е. Sulavko, Irina Panfilova, Daniil P. Inivatov, П. С. Ложников, Alexey Vulfin, Alexander Samotuga · Applied System Innovation · 2025
This work is devoted to the development of a biometric authentication system and the generation of a cryptographic key or a long password of 1024 bits based on a voice password, which ensures the protection of a biometric template from compromise. A new hybrid neural network model based on two types of trigonometric correlation neurons was proposed. The model is capable of recording correlation links between features and is resistant to data extraction attacks. The experiments were conducted on our own AIC-spkr-130 dataset and the publicly available RedDots, including recordings of user voices in different psycho-emotional states (sleepy state, alcohol intoxication). The results show that the proposed neural fuzzy extractor model provides an equal error probability level of EER = 2.1%.