| dc.contributor.author | Pryimak, A. | en |
| dc.contributor.author | Yaremchuk, Yu. | en |
| dc.contributor.author | Salieva, O. | en |
| dc.contributor.author | Karpinets, V. | en |
| dc.contributor.author | Kunanets, N. | en |
| dc.contributor.author | Приймак, А. В. | uk |
| dc.contributor.author | Яремчук, Ю. Є. | uk |
| dc.contributor.author | Салієва, О. В. | uk |
| dc.contributor.author | Карпінець, В. В. | uk |
| dc.contributor.author | Кунанець, Н. | uk |
| dc.date.accessioned | 2021-11-25T08:12:03Z | |
| dc.date.available | 2021-11-25T08:12:03Z | |
| dc.date.issued | 2021 | |
| dc.identifier.citation | Method of user authentication by keyboard handwriting based on neural networks and genetic algorithm [Electronic resource] / A. Pryimak, Yu. Yaremchuk, O. Salieva [et al.] // Proceedings of the International Workshop of IT-professionals on Artificial Intelligence (ProfIT AI 2021), September 20-21, 2021. – Kharkiv, 2021. – Р. 141-149. | en |
| dc.identifier.citation | Pryimak A., Yaremchuk Yu., Salieva O., Karpinets V., Kunanets N. Method of user authentication by keyboard handwriting based on neural networks and genetic algorithm. Proceedings of the International Workshop of IT-professionals on Artificial Intelligence (ProfIT AI 2021), September 20-21, 2021. Kharkiv, 2021. Р. 141-149. | en |
| dc.identifier.citation | Method of user authentication by keyboard handwriting based on neural networks and genetic algorithm [Text] / A. Pryimak, Yu. Yaremchuk, O. Salieva [etc.] // Proceedings of the International Workshop of IT-professionals on Artificial Intelligence (ProfIT AI 2021), September 20-21, 2021. – Kharkiv, 2021. – Р. 141-149. | en |
| dc.identifier.uri | http://ir.lib.vntu.edu.ua//handle/123456789/34543 | |
| dc.description.abstract | A method of user authentication based on keyboard handwriting with error injection was
proposed. It is based on a two-level neural network architecture using five-time functions
and built-in sigmoid activation function to increase the efficiency of the neural network.
An error code injection was also introduced, which allowed to collect more accurate data
on human handwriting and increase the accuracy of correct recognition of the user and his
successful authentication by 3-11% compared to existing methods. The use of a hash
function based on a genetic algorithm is proposed, which provides the security of storing
a code word in the database | en |
| dc.language.iso | en | en |
| dc.publisher | National Aerospace University "Kharkiv Aviation Institute" | en |
| dc.relation.ispartof | Proceedings of the International Workshop of IT-professionals on Artificial Intelligence (ProfIT AI 2021), September 20-21, 2021 : 141-149. | en |
| dc.subject | information security | en |
| dc.subject | user authentication | en |
| dc.subject | neural network | en |
| dc.subject | keyboard handwriting | en |
| dc.subject | genetic algorithm | en |
| dc.title | Method of user authentication by keyboard handwriting based on neural networks and genetic algorithm | en |
| dc.type | Article | |
