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Talk · IEEE International Conference on Smart Information Systems and Technologies · May 15, 2024

Research and development of two-factor authentication methods using neural networks

Temirkhan Darbek, Assel Mukasheva, Alibek Bissembayev, Sergiy O. Gnatyuk, Dinargul Mukammejanova

Assel Mukasheva
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Abstract

This article is devoted to the research and development of innovative two-factor authentication (2FA) methods using neural networks. 2FA plays a key role in ensuring the security of data and accounts in the modern digital world, and the use of neural networks opens up new prospects in strengthening protection and improving the user experience. The article presents an analysis of existing 2FA methods, identifies their limitations, and discusses the advantages of using neural networks in this area. The main focus is on the development of new authentication algorithms based on deep learning, providing effective anomaly detection and support for a dynamic adaptive approach. In the context of the article, the issues of privacy and data security are also considered, as well as the possibilities of applying the developed methods in various fields, including finance, medicine and the Internet of Things. The results of the study represent a significant contribution to the field of digital

User Authentication and Security SystemsAdvanced Authentication Protocols SecurityBiometric Identification and Securitytwo-factor authenticationartificial neural networksanomaly detection

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