{"id":4648,"date":"2021-03-12T14:00:25","date_gmt":"2021-03-12T12:00:25","guid":{"rendered":"http:\/\/journals.khnu.km.ua\/vestnik\/?p=4648"},"modified":"2021-03-17T12:21:01","modified_gmt":"2021-03-17T10:21:01","slug":"%d0%b7%d0%b0%d1%81%d1%82%d0%be%d1%81%d1%83%d0%b2%d0%b0%d0%bd%d0%bd%d1%8f-%d0%b1%d0%b0%d0%b3%d0%b0%d1%82%d0%be%d1%84%d0%b0%d0%ba%d1%82%d0%be%d1%80%d0%bd%d0%be%d0%b3%d0%be-%d0%b0%d0%bd%d0%b0%d0%bb%d1%96","status":"publish","type":"post","link":"https:\/\/journals.khnu.km.ua\/vestnik\/?p=4648","title":{"rendered":"\u0417\u0430\u0441\u0442\u043e\u0441\u0443\u0432\u0430\u043d\u043d\u044f \u0431\u0430\u0433\u0430\u0442\u043e\u0444\u0430\u043a\u0442\u043e\u0440\u043d\u043e\u0433\u043e \u0430\u043d\u0430\u043b\u0456\u0437\u0443 \u0437 \u043c\u0435\u0442\u043e\u044e \u0432\u0438\u044f\u0432\u043b\u0435\u043d\u043d\u044f \u043d\u0435\u0437\u0430\u0434\u043e\u043a\u0443\u043c\u0435\u043d\u0442\u043e\u0432\u0430\u043d\u0438\u0445 \u0437\u0430\u043a\u043b\u0430\u0434\u043e\u043a \u043f\u0440\u043e\u0433\u0440\u0430\u043c\u043d\u043e\u0433\u043e \u0437\u0430\u0431\u0435\u0437\u043f\u0435\u0447\u0435\u043d\u043d\u044f \u0432 \u043b\u043e\u043a\u0430\u043b\u044c\u043d\u0438\u0445 \u043a\u043e\u043c\u043f\u2019\u044e\u0442\u0435\u0440\u043d\u0438\u0445 \u043c\u0435\u0440\u0435\u0436\u0430\u0445"},"content":{"rendered":"

<\/p>\n

\u0417\u0410\u0421\u0422\u041e\u0421\u0423\u0412\u0410\u041d\u041d\u042f \u0411\u0410\u0413\u0410\u0422\u041e\u0424\u0410\u041a\u0422\u041e\u0420\u041d\u041e\u0413\u041e \u0410\u041d\u0410\u041b\u0406\u0417\u0423 \u0417 \u041c\u0415\u0422\u041e\u042e \u0412\u0418\u042f\u0412\u041b\u0415\u041d\u041d\u042f \u041d\u0415\u0417\u0410\u0414\u041e\u041a\u0423\u041c\u0415\u041d\u0422\u041e\u0412\u0410\u041d\u0418\u0425 \u0417\u0410\u041a\u041b\u0410\u0414\u041e\u041a \u041f\u0420\u041e\u0413\u0420\u0410\u041c\u041d\u041e\u0413\u041e \u0417\u0410\u0411\u0415\u0417\u041f\u0415\u0427\u0415\u041d\u041d\u042f \u0412 \u041b\u041e\u041a\u0410\u041b\u042c\u041d\u0418\u0425 \u041a\u041e\u041c\u041f\u2019\u042e\u0422\u0415\u0420\u041d\u0418\u0425 \u041c\u0415\u0420\u0415\u0416\u0410\u0425<\/p>\n

APPLICATION OF MULTIFACTOR ANALYSIS FOR THE PURPOSE OF DETECTING IMPLANT IN THE SOFTWARE IN LOCAL COMPUTER NETWORKS<\/p>\n

\"\"<\/a> \u0421\u0442\u043e\u0440\u0456\u043d\u043a\u0438: 280-285. \u041d\u043e\u043c\u0435\u0440: \u21165, 2020 (289)<\/strong>
\n\u0410\u0432\u0442\u043e\u0440\u0438:<\/strong>
\n\u0412. \u041f.\u00a0\u041f\u0410\u042e\u041a, \u041e. \u0412. \u0413\u0415\u0419\u0414\u0410\u0420\u041e\u0412\u0410, \u0412. \u0414. \u041a\u041e\u0421\u0415\u041d\u041a\u041e\u0412, \u041e. \u0421. \u0421\u0410\u0412\u0415\u041d\u041a\u041e
\n\u0425\u043c\u0435\u043b\u044c\u043d\u0438\u0446\u044c\u043a\u0438\u0439 \u043d\u0430\u0446\u0456\u043e\u043d\u0430\u043b\u044c\u043d\u0438\u0439 \u0443\u043d\u0456\u0432\u0435\u0440\u0441\u0438\u0442\u0435\u0442
\nV. PAIUK , O. \u041dE\u0406DAROVA, V. KOSENKOV, O. SAVENKO
\nKhmelnytskyi National University
\nDOI:<\/strong> https:\/\/www.doi.org\/10.31891\/2307-5732-2020-289-5-280-285<\/a>
\n\u0420\u0435\u0446\u0435\u043d\u0437\u0456\u044f\/Peer review :<\/strong> 16.10.2020 \u0440.
\n\u041d\u0430\u0434\u0440\u0443\u043a\u043e\u0432\u0430\u043d\u0430\/Printed :<\/strong> 27.11.2020 \u0440.<\/p>\n

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\n\u041a\u043b\u044e\u0447\u043e\u0432\u0456 \u0441\u043b\u043e\u0432\u0430:<\/strong> \u043d\u0435\u0437\u0430\u0434\u043e\u043a\u0443\u043c\u0435\u043d\u0442\u043e\u0432\u0430\u043d\u0456 \u0437\u0430\u043a\u043b\u0430\u0434\u043a\u0438, \u043f\u0440\u043e\u0433\u0440\u0430\u043c\u043d\u0435 \u0437\u0430\u0431\u0435\u0437\u043f\u0435\u0447\u0435\u043d\u043d\u044f, \u0431\u0430\u0433\u0430\u0442\u043e\u0444\u0430\u043a\u0442\u043e\u0440\u043d\u0438\u0439 \u0430\u043d\u0430\u043b\u0456\u0437, \u0437\u043b\u043e\u0432\u043c\u0438\u0441\u043d\u0435 \u043f\u0440\u043e\u0433\u0440\u0430\u043c\u043d\u0435 \u0437\u0430\u0431\u0435\u0437\u043f\u0435\u0447\u0435\u043d\u043d\u044f, \u043b\u043e\u043a\u0430\u043b\u044c\u043d\u0430 \u043a\u043e\u043c\u043f\u2019\u044e\u0442\u0435\u0440\u043d\u0430 \u043c\u0435\u0440\u0435\u0436\u0430.<\/p>\n

\u0420\u043e\u0437\u0448\u0438\u0440\u0435\u043d\u0430 \u0430\u043d\u043e\u0442\u0430\u0446\u0456\u044f \u0430\u043d\u0433\u043b\u0456\u0439\u0441\u044c\u043a\u043e\u044e \u043c\u043e\u0432\u043e\u044e<\/strong><\/p>\n

The paper investigates strategies for detecting undocumented bookmarks in software, which may be independent objects or part of certain malicious software. Local computer networks were chosen as the place of research. The difficulty of detecting such a secretly included in the software functional object, which under certain conditions is able to provide unauthorized software influence, due to the possibility of its absence for a long time. Such an object can be part of a software package that performs tasks, replace completely certain parts of the software package, replace a certain required program. As a rule, such undocumented software bookmarks allow to store the software functions declared by the manufacturer and are realized by a part of functions which are a part of a software complex. The application of multifactor analysis methods to detect undocumented software bookmarks has been studied. This allowed the results to be applied to undocumented software bookmarks that are part of certain malware obtained for it by using a distributed multi-level detection system. In economic research, a taxonomic indicator of the level of development is used to compare objects that are characterized by a large number of features. In this case, it may be an indicator of the presence of undocumented software bookmarks on the local network. It is based on the taxonomic method of processing statistical data of observations, which is used in economic research. In this case, the objects are computer networks, and the signs may be: the presence of software modules that do not meet the purpose of the process; the presence of elements of operating systems that are open to the process, which do not meet the purpose of the process; high intensity of input-output operations from a certain process, etc. The result of improved detection results was confirmed by a long-term experiment to detect undocumented software bookmarks.
\nKeywords:<\/strong> implant, software, multifactor analysis, malicious software, local computer network.<\/p>\n

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