Machine learning based network traffic classification approach for Internet of Things devices

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dc.contributor.authorMelnik, Vadym
dc.contributor.authorHaleta, Pavlo
dc.contributor.authorGolphamid, Nazar
dc.date.accessioned2020-10-15T15:18:53Z
dc.date.available2020-10-15T15:18:53Z
dc.date.issued2020
dc.description.abstractenDue to design flaws, problems with implementations and improper network configuration, the Internet of Things devices become vulnerable in the network. They can be easily compromised and can also be attached to the Botnet network. IoT devices classification allows for strengthening of the overall network security through better VLAN planning and better firewall rule fine-tuning (e.g. per device class). In this paper only two classes of devices are considered: single-purpose devices (such as a bulb) and multi-purpose devices (such as mobile phone). Existing solutions do not provide the required accuracy within the given timeframe. We propose ML-based classification method based on supervised machine learning technology (Random Forest). With advanced packets flow analysis, our proposed approach demonstrates 94% of accuracy (7% better than the existing prior art). Additionally a very low False Positive rate is guaranteed for single-purpose IoT devices (e.g. a bulb must never be classified as a multi-purpose device).uk
dc.format.pagerangePp. 63-69uk
dc.identifier.citationMelnik, V. Machine learning based network traffic classification approach for Internet of Things devices / Vadym Melnik, Pavlo Haleta, Nazar Golphamid // Theoretical and Applied Cybersecurity : scientific journal. – 2020. – Vol. 2, Iss. 1. – Pp. 63–69. – Bibliogr.: 11 ref.uk
dc.identifier.doihttps://doi.org/10.20535/tacs.2664-29132020.1.209472
dc.identifier.urihttps://ela.kpi.ua/handle/123456789/36795
dc.language.isoenuk
dc.publisherIgor Sikorsky Kyiv Polytechnic Instituteuk
dc.publisher.placeKyivuk
dc.sourceTheoretical and Applied Cybersecurity : scientific journal, 2020, Vol. 2, No. 1uk
dc.subjectInternet of thingsuk
dc.subjectmachine learninguk
dc.subjectlocal networkuk
dc.subjectinternet trafficuk
dc.subjectcontrol packetuk
dc.subject.udc004.7:004.8uk
dc.titleMachine learning based network traffic classification approach for Internet of Things devicesuk
dc.typeArticleuk

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Theoretical and Applied Cybersecurity: scientific journal, Vol. 2, No. 1