Application of neural network technologies for user authentication in modern mobile systems
Abstract
Application of neural network technologies for user authentication in modern mobile systems
Incoming article date: 14.12.2024With the rapid development of mobile technologies and increasing risks of data leakage, providing reliable user authentication becomes one of the key tasks of information security. This paper is devoted to the study of application of neural network technologies for biometric authentication in modern mobile systems. The paper provides a comprehensive analysis of existing biometric authentication methods such as face recognition, voice and fingerprint analysis. Special attention is paid to the peculiarities of the methods' operation, accuracy and resistance to attacks. The main advantages and disadvantages of each of the considered authentication methods are given. At the end of the article is presented the practical application of the developed algorithm of neural network authentication based on fingerprint analysis, integrated into the SIM-card. This innovative approach not only increases the security level of mobile devices, but also provides convenience to the user. The implementation of this case study will form the basis for further research presented in this thesis work, which emphasizes the importance of integrating neural network technologies into authentication processes. The results of the research will be useful for both scientists and developers in the field of information security, opening new horizons for the improvement of biometric systems in the mobile environment.
Keywords: authentication, neural networks, biometrics, mobile systems, information security, deepfake, GDPR, hybrid technologies, sim card