{"id":4731,"date":"2021-03-12T14:28:02","date_gmt":"2021-03-12T12:28:02","guid":{"rendered":"http:\/\/journals.khnu.km.ua\/vestnik\/?p=4731"},"modified":"2021-03-16T12:20:35","modified_gmt":"2021-03-16T10:20:35","slug":"%d0%bc%d1%83%d0%bb%d1%8c%d1%82%d0%b8%d0%b0%d0%b3%d0%b5%d0%bd%d1%82%d0%bd%d0%b0-%d1%81%d0%b8%d1%81%d1%82%d0%b5%d0%bc%d0%b0-%d0%bf%d0%be%d0%b7%d0%b8%d1%86%d1%96%d0%be%d0%bd%d1%83%d0%b2%d0%b0%d0%bd%d0%bd","status":"publish","type":"post","link":"https:\/\/journals.khnu.km.ua\/vestnik\/?p=4731","title":{"rendered":"\u041c\u0443\u043b\u044c\u0442\u0438\u0430\u0433\u0435\u043d\u0442\u043d\u0430 \u0441\u0438\u0441\u0442\u0435\u043c\u0430 \u043f\u043e\u0437\u0438\u0446\u0456\u043e\u043d\u0443\u0432\u0430\u043d\u043d\u044f \u0440\u0443\u0445\u043e\u043c\u0438\u0445 \u043e\u0431\u2019\u0454\u043a\u0442\u0456\u0432 \u044f\u043a \u0445\u043e\u0441\u0442\u0456\u0432 \u0431\u0435\u0437\u0434\u0440\u043e\u0442\u043e\u0432\u043e\u0457 \u043c\u0435\u0440\u0435\u0436\u0456"},"content":{"rendered":"

<\/p>\n

\u041c\u0423\u041b\u042c\u0422\u0418\u0410\u0413\u0415\u041d\u0422\u041d\u0410 \u0421\u0418\u0421\u0422\u0415\u041c\u0410 \u041f\u041e\u0417\u0418\u0426\u0406\u041e\u041d\u0423\u0412\u0410\u041d\u041d\u042f \u0420\u0423\u0425\u041e\u041c\u0418\u0425 \u041e\u0411\u2019\u0404\u041a\u0422\u0406\u0412 \u042f\u041a \u0425\u041e\u0421\u0422\u0406\u0412 \u0411\u0415\u0417\u0414\u0420\u041e\u0422\u041e\u0412\u041e\u0407 \u041c\u0415\u0420\u0415\u0416\u0406<\/p>\n

MULTIAGENT SYSTEM FOR POSITIONING OF MOBILE OBJECTS AS WIRELESS NETWORK HOSTS<\/p>\n

\"\"<\/a> \u0421\u0442\u043e\u0440\u0456\u043d\u043a\u0438: 72-80. \u041d\u043e\u043c\u0435\u0440: \u21165, 2020 (289)<\/strong>
\n\u0410\u0432\u0442\u043e\u0440\u0438:<\/strong>
\n\u0406.\u0421. \u0411\u0423\u0420\u041b\u0410\u0427\u0415\u041d\u041a\u041e, \u0412.\u042e. \u0421\u0410\u0412\u0406\u041d\u041e\u0412, \u041e.\u0420. \u0422\u041e\u0413\u041e\u0404\u0412
\n\u0427\u043e\u0440\u043d\u043e\u043c\u043e\u0440\u0441\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 \u0456\u043c\u0435\u043d\u0456 \u041f\u0435\u0442\u0440\u0430 \u041c\u043e\u0433\u0438\u043b\u0438, \u043c. \u041c\u0438\u043a\u043e\u043b\u0430\u0457\u0432
\nI. BURLACHENKO, V. SAVINOV, O. TOHOIEV
\nPetro Mohyla Black Sea National University
\nDOI:<\/strong> https:\/\/www.doi.org\/10.31891\/2307-5732-2020-289-5-72-80<\/a>
\n\u0420\u0435\u0446\u0435\u043d\u0437\u0456\u044f\/Peer review :<\/strong> 19.10.2020 \u0440.
\n\u041d\u0430\u0434\u0440\u0443\u043a\u043e\u0432\u0430\u043d\u0430\/Printed :<\/strong> 27.11.2020 \u0440.<\/p>\n

\u0410\u043d\u043e\u0442\u0430\u0446\u0456\u044f \u043c\u043e\u0432\u043e\u044e \u043e\u0440\u0438\u0433\u0456\u043d\u0430\u043b\u0443<\/strong><\/p>\n

\u0423 \u0441\u0442\u0430\u0442\u0442\u0456 \u0440\u043e\u0437\u0433\u043b\u044f\u043d\u0443\u0442\u043e \u043c\u0435\u0442\u043e\u0434\u0438 \u0432\u0438\u0437\u043d\u0430\u0447\u0435\u043d\u043d\u044f \u043f\u043e\u0437\u0438\u0446\u0456\u043e\u043d\u0443\u0432\u0430\u043d\u043d\u044f \u0440\u0443\u0445\u043e\u043c\u0438\u0445 \u043e\u0431\u2019\u0454\u043a\u0442\u0456\u0432 \u0443 \u043f\u0440\u043e\u0441\u0442\u043e\u0440\u0456. \u041f\u043e\u043a\u0430\u0437\u0430\u043d\u043e, \u0449\u043e \u043b\u043e\u043a\u0430\u043b\u0456\u0437\u0430\u0446\u0456\u044f \u043e\u0431\u2019\u0454\u043a\u0442\u0456\u0432 \u043d\u0430 \u043e\u0441\u043d\u043e\u0432\u0456 Wi-Fi \u0454 \u043e\u0434\u043d\u0438\u043c \u0437 \u043d\u0430\u0439\u043f\u043e\u043f\u0443\u043b\u044f\u0440\u043d\u0456\u0448\u0438\u0445 \u0440\u0456\u0448\u0435\u043d\u044c \u0456 \u0432\u0432\u0430\u0436\u0430\u0454\u0442\u044c\u0441\u044f \u043d\u0430\u0439\u0431\u0456\u043b\u044c\u0448 \u043f\u0435\u0440\u0441\u043f\u0435\u043a\u0442\u0438\u0432\u043d\u0438\u043c. \u0422\u0435\u043e\u0440\u0435\u0442\u0438\u0447\u043d\u043e \u043e\u0431\u0491\u0440\u0443\u043d\u0442\u043e\u0432\u0430\u043d\u043e \u0442\u0430 \u0440\u043e\u0437\u0433\u043b\u044f\u043d\u0443\u0442\u043e \u043f\u0440\u0430\u043a\u0442\u0438\u0447\u043d\u0443 \u0440\u0435\u0430\u043b\u0456\u0437\u0430\u0446\u0456\u044e WiFi-\u0441\u043d\u0456\u0444\u0444\u0435\u0440\u0443 \u0434\u043b\u044f \u0432\u0438\u0437\u043d\u0430\u0447\u0435\u043d\u043d\u044f \u0440\u043e\u0437\u0442\u0430\u0448\u0443\u0432\u0430\u043d\u043d\u044f \u0440\u0443\u0445\u043e\u043c\u0438\u0445 \u043e\u0431’\u0454\u043a\u0442\u0456\u0432, \u043f\u0456\u0434\u043a\u043b\u044e\u0447\u0435\u043d\u0438\u0445 \u0434\u043e \u0431\u0435\u0437\u0434\u0440\u043e\u0442\u043e\u0432\u043e\u0457 \u043c\u0435\u0440\u0435\u0436\u0456. \u0420\u043e\u0437\u0440\u043e\u0431\u043b\u0435\u043d\u043e \u0430\u043b\u0433\u043e\u0440\u0438\u0442\u043c \u0444\u0456\u043a\u0441\u0430\u0446\u0456\u0457 \u0440\u043e\u0437\u0442\u0430\u0448\u0443\u0432\u0430\u043d\u043d\u044f \u043e\u0431\u2019\u0454\u043a\u0442\u0456\u0432 \u0448\u043b\u044f\u0445\u043e\u043c \u0457\u0445 \u0456\u0434\u0435\u043d\u0442\u0438\u0444\u0456\u043a\u0430\u0446\u0456\u0457 \u0437\u0430 \u0434\u043e\u043f\u043e\u043c\u043e\u0433\u043e\u044e \u043d\u0435\u0439\u0440\u043e\u043d\u043d\u043e\u0457 \u043c\u0435\u0440\u0435\u0436\u0456 \u0437 \u0432\u0438\u043a\u043e\u0440\u0438\u0441\u0442\u0430\u043d\u043d\u044f\u043c \u0437\u0430\u043f\u0440\u043e\u043f\u043e\u043d\u043e\u0432\u0430\u043d\u043e\u0457 \u043c\u0443\u043b\u044c\u0442\u0438\u0430\u0433\u0435\u043d\u0442\u043d\u043e\u0457 \u043c\u043e\u043d\u0456\u0442\u043e\u0440\u0438\u043d\u0433\u043e\u0432\u043e\u0457 \u0441\u0438\u0441\u0442\u0435\u043c\u0438.
\n\u041a\u043b\u044e\u0447\u043e\u0432\u0456 \u0441\u043b\u043e\u0432\u0430:<\/strong> Wi-Fi \u0441\u043d\u0456\u0444\u0444\u0435\u0440, \u043f\u043e\u0437\u0438\u0446\u0456\u043e\u043d\u0443\u0432\u0430\u043d\u043d\u044f \u0440\u0443\u0445\u043e\u043c\u043e\u0433\u043e \u043e\u0431\u2019\u0454\u043a\u0442\u0430, \u043c\u0443\u043b\u044c\u0442\u0438\u0430\u0433\u0435\u043d\u0442\u043d\u0430 \u043c\u043e\u043d\u0456\u0442\u043e\u0440\u0438\u043d\u0433\u043e\u0432\u0430 \u0441\u0438\u0441\u0442\u0435\u043c\u0430, \u043c\u043e\u0434\u0435\u043b\u044c \u0434\u043e\u0432\u0433\u043e\u0441\u0442\u0440\u043e\u043a\u043e\u0432\u043e\u0457 \u043f\u0430\u043c\u2019\u044f\u0442\u0456.<\/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 purpose of the work is to theoretically substantiate and practically implement the capabilities of WiFi-sniffing to determine the location of objects. Also, it was set a aim to develop an algorithm for fixing the location of moving objects connected to a wireless network by identifying them using a neural network. The expediency of using a comprehensive positioning technology based on IEEE 802.11 (Wi Fi) and a multi-agent approach was substantiated to solve the task of positioning and identification. The proposed multiagent approach takes into account the multifaceted nature of the radio channel when calculating the characteristics of the signal during communication of moving objects direct and through access points (AP). The authors proposed a model based on long short-term memory (LSTM), which was included as a directional acyclic graph (DAG) layer and used to identify the behavior of agents of a multi-agent monitoring system (MAMS). To solve the problem of categorization, it was proposed using the Keras model in agent logic based on subnet addresses and agent categories. The developed software allows to track moving objects (smartphones or other gadgets) that are in different segments of the network in relation to a router and host sniffer. These theoretical calculations are confirmed in practice to determine the location of moving objects having access to the Internet – via Wi-Fi or Ethernet – as mobile devices. According to the obtained data, the proposed model has showed 98.7% accuracy in classification. In addition, with this approach, it is possible to reduce the number of calculations in the model. It was also considered the alternative methods for determining the positioning of moving objects in systems with a high level of information security, which exclude the possibility of radio communication.
\nKeywords:<\/strong> Wi-Fi Sniffer, Positioning of Mobile Objects, Multiagent Monitoring System (MAMS), Long Short-Term Memory (LSTM)<\/p>\n

References<\/strong><\/p>\n

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