NETWORK TRAFFIC ANALYSIS WITH GENETIC ALGORITHMS

dc.contributor.author	Ibrohimov Azizbek Ravshonbek o‘g‘li
dc.contributor.author	Haydarov Elshod Dilshod o‘g‘li
dc.date.accessioned	2025-12-28T13:15:39Z
dc.date.issued	2025-10-27
dc.description.abstract	This article analyzes the possibilities of using genetic algorithms in detecting network attacks. The genetic algorithm improves efficiency in selecting network attributes and adjusting model parameters as an optimization method based on evolutionary principles. The study highlighted the most important traits through selection, cross-over, and mutation mechanisms, resulting in improved attack accuracy by up to 97%. As a result, the genetic approach significantly improves the accuracy of the IDS system.
dc.format	application/pdf
dc.identifier.uri	https://brightmindpublishing.com/index.php/EI/article/view/1534
dc.identifier.uri	https://asianeducationindex.com/handle/123456789/6226
dc.language.iso	eng
dc.publisher	Bright Mind Publishing
dc.relation	https://brightmindpublishing.com/index.php/EI/article/view/1534/1560
dc.rights	https://creativecommons.org/licenses/by/4.0
dc.source	Educator Insights: Journal of Teaching Theory and Practice; Vol. 1 No. 10 (2025); 308-313
dc.source	3061-6964
dc.subject	Genetic algorithm, optimization, network attacks, anomaly detection, cross-over, mutation, attribute selection, IDS system.
dc.title	NETWORK TRAFFIC ANALYSIS WITH GENETIC ALGORITHMS
dc.type	info:eu-repo/semantics/article
dc.type	info:eu-repo/semantics/publishedVersion
dc.type	Peer-reviewed Article

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