Please use this identifier to cite or link to this item: http://ir.futminna.edu.ng:8080/jspui/handle/123456789/15637
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dc.contributor.authorMaikudi, Umar-
dc.contributor.authorAbisoye, Opeyemi Aderiike-
dc.contributor.authorGaniyu, Shefiu Olusegun-
dc.contributor.authorBashir, Sulaimon A.-
dc.date.accessioned2022-12-20T14:48:07Z-
dc.date.available2022-12-20T14:48:07Z-
dc.date.issued2021-
dc.identifier.urihttp://repository.futminna.edu.ng:8080/jspui/handle/123456789/15637-
dc.description.abstractOne of the significant security concerns in the Information Technology community is Botnet, which could be used by adversaries to launch different kinds of attacks from compromised IoT devices. Botnets were initially created for positive purposes, not until cybercriminals began to take advantage of their potentials and started programming malicious software for malicious intent thereby, making detection and mitigation difficult. The rapid rise in the development of IoT products has made cyber-attack permutations unpredictable and availed cybercriminals of new techniques for security breaches of such products. Hence, the motivation for this research is premised on the incessant increase in the botnet attacks on IoT-based products. Thus, this paper offers a comprehensive literature overview of current IoT botnet detection techniques with a focus on revealing the strengths and weaknesses of the existing techniques in the research area. In line with this, some selected techniques were retrieved and analyzed in the summary table and a conclusion is drawn which exposed the need for more robust detection techniques to detect and prevent the emerging sophisticated botnet versions in the domain. Therefore, the findings from this review will benefits researchers who are engaged in detecting and preventing botnet attacks over IoT devices and network.en_US
dc.language.isoenen_US
dc.publisher4th International Conference on Information Technology in Education and Developmenten_US
dc.subjectBotnet Detectionen_US
dc.subjectIoT Devicesen_US
dc.subjectC&C Channelen_US
dc.subjectBotmasteren_US
dc.subjectDetection Techniquesen_US
dc.titleA Literature Survey on IoT Botnet Detection Techniquesen_US
dc.typeArticleen_US
Appears in Collections:Information and Media Technology

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