Title | Learning neural network for multi-factor authentication using biometric technologies |
---|---|

Authors | A. S. Ismagilova^{1}, N. D. Lushnikov^{1}^{1}Bashkir State University |

Annotation | The article considers and applies a method for synthesizing the parameters of convolutional neural network represented in the form of unique personal computer user identifiers. For full-fledged protection of information resources the authors have implemented training of the training model using categorical cross-entropy. The main purpose of the study is to explore new aspects of mathematical modeling of the information protection system. The task of this study is the software implementation of the mathematical model of multifactor authentication using biometric technology, which is necessary to improve the integrated information security system. |

Keywords | mathematical model, information protection system, account, user, security, artificial intelligence, identification, biometrics. |

Citation | Ismagilova A. S., Lushnikov N. D. ''Learning neural network for multi-factor authentication using biometric technologies'' [Electronic resource]. Proceedings of the International Scientific Youth School-Seminar "Mathematical Modeling, Numerical Methods and Software complexes" named after E.V. Voskresensky (Saransk, July 14-18, 2022). Saransk: SVMO Publ, 2022. - pp. 104-110. Available at: https://conf.svmo.ru/files/2022/papers/paper16.pdf. - Date of access: 04.12.2023. |

**© SVMO, National Research Mordovia State University, 2023**

Powered by Yii Framework