Detection of Man-in-the-Middle Attack Through Artificial Intelligence Algorithm

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dc.authorscopusid58658407000
dc.authorscopusid57201743399
dc.authorscopusid57447588400
dc.authorscopusid6603658187
dc.authorscopusid57223927687
dc.authorscopusid57194619312
dc.contributor.authorTaştan, Ahmet Nail
dc.contributor.authorGönen, Serkan
dc.contributor.authorBarışkan, Mehmet Ali
dc.contributor.authorKubat, Cemallettin
dc.contributor.authorKaplan, Derya Yıltaş
dc.contributor.authorPashaei, Elham
dc.date.accessioned2024-09-11T19:58:23Z
dc.date.available2024-09-11T19:58:23Z
dc.date.issued2024
dc.departmentİstanbul Gelişim Üniversitesien_US
dc.description12th International Symposium on Intelligent Manufacturing and Service Systems, IMSS 2023 -- 26 May 2023 through 28 May 2023 -- Istanbul -- 302369en_US
dc.description.abstractThe amalgamation of information technologies and progressive wireless communication systems has profoundly impacted various facets of everyday life, encompassing communication mediums, occupational procedures, and living standards. This evolution, combined with enhanced wireless communication quality, has culminated in an exponential rise in interconnected devices, including domestic appliances, thereby birthing the Internet of Things (IoT) era. This proliferation, facilitated by cloud computing enabling remote device control, concurrently intensifies cybersecurity threats. Traditional Information and Communication Technology (ICT) architectures, characterized by a hub-and-spoke model, are inherently vulnerable to illicit access and Man-in-the-Middle (MITM) intrusions, thereby endangering information confidentiality. Leveraging Artificial Intelligence (AI) can ameliorate this scenario, enhancing threat training and detection capabilities, enabling precise and preemptive attack countermeasures. This research underscores the criticality of addressing the security implications accompanying technological advancements and implementing protective measures. Deploying AI algorithms facilitates efficient passive attack identification and alleviates network device burdens. Specifically, this study scrutinized the ramifications of an MITM attack on the system, emphasizing the detection of this elusive threat using AI. Our findings attest to AI’s efficacy in detecting MITM attacks, promising significant contributions to future cybersecurity research. © 2024, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.en_US
dc.identifier.doi10.1007/978-981-99-6062-0_41
dc.identifier.endpage458en_US
dc.identifier.isbn978-981996061-3en_US
dc.identifier.issn2195-4356en_US
dc.identifier.scopus2-s2.0-85174631911en_US
dc.identifier.scopusqualityQ4en_US
dc.identifier.startpage450en_US
dc.identifier.urihttps://doi.org/10.1007/978-981-99-6062-0_41
dc.identifier.urihttps://hdl.handle.net/11363/8461
dc.indekslendigikaynakScopusen_US
dc.language.isoenen_US
dc.publisherSpringer Science and Business Media Deutschland GmbHen_US
dc.relation.ispartofLecture Notes in Mechanical Engineeringen_US
dc.relation.publicationcategoryKonferans Öğesi - Uluslararası - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.snmz20240903_Gen_US
dc.subjectArtificial Intelligence; Attack Detection; Cyber Security; Man-in-the-Middle Attacken_US
dc.titleDetection of Man-in-the-Middle Attack Through Artificial Intelligence Algorithmen_US
dc.typeConference Objecten_US

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