Публікація:
Розробка підходу до ідентифікації користувачів системи за їх поведінкою за допомогою методів машинного навчання

dc.contributor.authorКолтун, Ю. М.
dc.contributor.authorЄвстрат, Д. І.
dc.contributor.authorСєвєрінов, О. В.
dc.contributor.authorЛяшенко, О. С.  
dc.contributor.authorМартовицький, В. О.
dc.contributor.authorЛяшенко, С. О.
dc.contributor.authorКісь, В. М.
dc.contributor.authorСухотеплий, В. М.
dc.contributor.authorКонов, Д. В
dc.contributor.authorНосик, А. М.
dc.date.accessioned2022-07-18T20:38:12Z
dc.date.available2022-07-18T20:38:12Z
dc.date.issued2022
dc.description.abstractOne of the biggest reasons that lead to violations of the security of companies’ services is obtaining access by the intruder to the legitimate accounts of users in the system. It is almost impossible to fight this since the intruder is authorized as a legitimate user, which makes intrusion detection systems ineffective. Thus, the task to devise methods and means of protection (intrusion detection) that would make it possible to identify system users by their behavior becomes relevant. This will in no way protect against the theft of the data of the accounts of users of the system but will make it possible to counteract the intruders in cases where they use this account for further hacking of the system. The object of this study is the process of protecting system users in the case of theft of their authentication data. The subject is the process of identifying users of the system by their behavior in the system. This paper reports a functional model of the process of ensuring the identification of users by their behavior in the system, which makes it possible to build additional means of protecting system users in the case of theft of their authentication data. The identification model takes into consideration the statistical parameters of user behavior that were obtained during the session. In contrast to the existing approaches, the proposed model makes it possible to provide a comprehensive approach to the analysis of the behavior of users both during their work (in a real-time mode) and after the session is over (in a delayed mode). An experimental study on the proposed approach of identifying users by their behavior in the system showed that the built patterns of user behavior using machine learning methods demonstrated an assessment of the quality of identification exceeding 0.95uk_UA
dc.identifier.citationMartovytskyi, V., Sievierinov О., Liashenko, O., Koltun, Y., Liashenko, S., Kis, V., Sukhoteplyi, V., Nosyk, A., Konov, D., & Yevstrat, D. (2022). Devising an approach to the identification of system users by their behavior using machine learning methods . Eastern-European Journal of Enterprise Technologies, 3(3 (117), 23–34.uk_UA
dc.identifier.issn1729-4061
dc.identifier.urihttps://openarchive.nure.ua/handle/document/20710
dc.language.isoenuk_UA
dc.publisherEastern-European Journal of Enterprise Technologiesuk_UA
dc.subjectmachine learning methodsuk_UA
dc.subjectinformation protectionuk_UA
dc.subjectuser identificationuk_UA
dc.subjectbehavior modeluk_UA
dc.titleРозробка підходу до ідентифікації користувачів системи за їх поведінкою за допомогою методів машинного навчанняuk_UA
dc.typeArticleuk_UA
dspace.entity.typePublication

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