A Novel Approach to Prevention of Hello Flood Attack in IoT Using Machine Learning Algorithm

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dc.authorscopusid57201743399
dc.authorscopusid57447588400
dc.authorscopusid57203142239
dc.authorscopusid57773121800
dc.authorscopusid56469924100
dc.authorscopusid6504413319
dc.authorscopusid57203142641
dc.contributor.authorGönen, Serkan
dc.contributor.authorBarişkan, Mehmet Ali
dc.contributor.authorKaracayilmaz, Gökçe
dc.contributor.authorAlhan, Birkan
dc.contributor.authorYilmaz, Ercan Nurcan
dc.contributor.authorArtuner, Harun
dc.contributor.authorSindiren, Erhan
dc.date.accessioned2024-09-11T19:58:12Z
dc.date.available2024-09-11T19:58:12Z
dc.date.issued2022
dc.departmentİstanbul Gelişim Üniversitesien_US
dc.description.abstractWith the developments in information technologies, every area of our lives, from shopping to education, from health to entertainment, has transitioned to the cyber environment, defined as the digital environment. In particular, the concept of the Internet of Things (IoT) has emerged in the process of spreading the internet and the idea of controlling and managing every device based on IP. The fact that IoT devices are interconnected with limited resources causes users to become vulnerable to internal and external attacks that threaten their security. In this study, a Flood attack, which is an important attack type against IoT networks, is discussed. Within the scope of the analysis of the study, first of all, the effect of the flood attack on the system has been examined. Subsequently, it has been focused on detecting the at-tack through the K-means algorithm, a machine learning algorithm. The analysis results have been shown that the attacking mote where the flood attack has been carried out has been successfully detected. In this way, similar flood attacks will be detected as soon as possible, and the system will be saved from the attack with the most damage and will be activated as soon as possible. © 2022, TUBITAK. All rights reserved.en_US
dc.identifier.doi10.31202/ecjse.1149925
dc.identifier.endpage1541en_US
dc.identifier.issn2148-3736en_US
dc.identifier.issue4en_US
dc.identifier.scopus2-s2.0-85146780285en_US
dc.identifier.scopusqualityQ4en_US
dc.identifier.startpage1529en_US
dc.identifier.urihttps://doi.org/10.31202/ecjse.1149925
dc.identifier.urihttps://hdl.handle.net/11363/8442
dc.identifier.volume9en_US
dc.indekslendigikaynakScopusen_US
dc.language.isoenen_US
dc.publisherTUBITAKen_US
dc.relation.ispartofEl-Cezeri Journal of Science and Engineeringen_US
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/openAccessen_US
dc.snmz20240903_Gen_US
dc.subjectCyber Security; Flood Attacks; IoT; IoT Security; Machine learningen_US
dc.titleA Novel Approach to Prevention of Hello Flood Attack in IoT Using Machine Learning Algorithmen_US
dc.title.alternativeMakine Öğrenmesi Algoritmasını Kullanarak IoT'de Hello Flood Saldırısının Önlenmesine Yönelik Yeni Bir Yaklaşım]en_US
dc.typeArticleen_US

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