BIOMETRIC AUTHENTICATION UTILIZING CONVOLUTIONAL NEURAL NETWORKS

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Abstract

Relevance. Cryptographic algorithms and protocols are important tools in modern cybersecurity. They are used in various applications, from simple software for encrypting computer information to complex information and telecommunications systems that implement various electronic trust services. Developing complete biometric cryptographic systems will allow using personal biometric data as a unique secret parameter instead of needing to remember cryptographic keys or using additional authentication devices. The object of research the process of generating cryptographic keys from biometric images of a person's face with the implementation of fuzzy extractors. The subject of the research is the means and methods of building a neural network using modern technologies. The purpose of this paper to study new methods for generating cryptographic keys from biometric images using convolutional neural networks and histogram of oriented gradients. Research results. The proposed technology allows for the implementation of a new cryptographic mechanism-a technology for generating reliable cryptographic passwords from biometric images for further use as attributes for access to secure systems, as well as a source of keys for existing cryptographic algorithms.

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APA

Datsenko, S., & Kuchuk, H. (2023). BIOMETRIC AUTHENTICATION UTILIZING CONVOLUTIONAL NEURAL NETWORKS. Advanced Information Systems, 7(2), 87–91. https://doi.org/10.20998/2522-9052.2023.2.12

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