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Text Classification of Illegal Activities on Onion Sites

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dc.contributor.authorBuldin, I. D.
dc.contributor.authorIvanov, N. S.
dc.date.accessioned2024-11-25T18:07:40Z
dc.date.available2024-11-25T18:07:40Z
dc.date.issued2020
dc.description.abstract© 2020 IEEE.Onion sites work using the Hidden Service Protocol, which helps to keep a double anonymity. A such system allows sites to place malicious and illegal content. An identification and tracking of such resources is an important problem, that's why the article sets a task of developing a system for accurate thematic classification of textual content blocks of hidden web pages using k nearest neighbors method. The article presents the method of content separation placed on Russian-language onion-sites. The research illustrates the analysis of text categorization results based on collected dataset for the implementation of machine learning.
dc.format.extentС. 245-247
dc.identifier.citationBuldin, I. D. Text Classification of Illegal Activities on Onion Sites / Buldin, I.D., Ivanov, N.S. // Proceedings of the 2020 IEEE Conference of Russian Young Researchers in Electrical and Electronic Engineering, EIConRus 2020. - 2020. - P. 245-247. - 10.1109/EIConRus49466.2020.9039341
dc.identifier.doi10.1109/EIConRus49466.2020.9039341
dc.identifier.urihttps://www.doi.org/10.1109/EIConRus49466.2020.9039341
dc.identifier.urihttps://www.scopus.com/record/display.uri?eid=2-s2.0-85082984898&origin=resultslist
dc.identifier.urihttps://openrepository.mephi.ru/handle/123456789/20588
dc.relation.ispartofProceedings of the 2020 IEEE Conference of Russian Young Researchers in Electrical and Electronic Engineering, EIConRus 2020
dc.titleText Classification of Illegal Activities on Onion Sites
dc.typeConference Paper
dspace.entity.typePublication
relation.isOrgUnitOfPublication010157d0-1f75-46b2-ab5b-712e3424b4f5
relation.isOrgUnitOfPublication.latestForDiscovery010157d0-1f75-46b2-ab5b-712e3424b4f5
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