Machine learning algorithms for URLs classification

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dc.contributor.authorAl Zirjawi, Sabah Salam Khaduair
dc.contributor.authorKashkool, Hawraa Jaafar Murad
dc.contributor.authorIbrahim, Abdullahi Abdu
dc.contributor.authorAl, Mona Idan Ali
dc.date.accessioned2023-06-10T09:29:34Z
dc.date.available2023-06-10T09:29:34Z
dc.date.issued2022en_US
dc.departmentEnstitüler, Lisansüstü Eğitim Enstitüsü, Elektrik ve Bilgisayar Mühendisliği Ana Bilim Dalıen_US
dc.description.abstractPhishing is a technique used to collect sensitive data from a user (password or credit card information) for future misuse by posing as a trustworthy source. It often takes advantage of the user's gullibility in ways that the user will not detect at first look, and in the worst-case scenario, the attacker maintains the user's data without the user's awareness. Typically, the URL is the first and simplest piece of information we know about a website. As a result, it is logical to design algorithms for distinguishing harmful from benign URLs. Additionally, accessing and downloading the website's material may be time-consuming and involves the danger of downloading potentially hazardous information. Machine Learning techniques are used to train a model on a collection of URLs specified as a set of characteristics and then predict and categorize the URLs as benign or dangerous. This technology enables us to identify and avoid possibly dangerous URLs shortly.en_US
dc.identifier.citationAl Zirjawi, S. S. K., Kashkool, H. J. M., Ibrahim, A. A., & Al, M. I. A. (2022). Machine learning algorithms for URLs classification. In 2022 International Conference on Artificial Intelligence of Things (ICAIoT). IEEE.en_US
dc.identifier.isbn9798350396768
dc.identifier.scopus2-s2.0-85160514303
dc.identifier.scopusqualityN/A
dc.identifier.urihttps://hdl.handle.net/20.500.12939/3535
dc.indekslendigikaynakScopus
dc.institutionauthorAl Zirjawi, Sabah Salam Khaduair
dc.institutionauthorKashkool, Hawraa Jaafar Murad
dc.institutionauthorIbrahim, Abdullahi Abdu
dc.institutionauthorAl, Mona Idan Ali
dc.language.isoen
dc.publisherInstitute of Electrical and Electronics Engineers Inc.en_US
dc.relation.ispartofProceedings - 2022 International Conference on Artificial Intelligence of Things, ICAIoT 2022
dc.relation.isversionof10.1109/ICAIoT57170.2022.10121843en_US
dc.relation.publicationcategoryKonferans Öğesi - Uluslararası - İdari Personel ve Öğrencien_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.subjectFeature Extractionen_US
dc.subjectKNNen_US
dc.subjectLogistic Regressionen_US
dc.subjectNaïve Bayesen_US
dc.subjectSVMen_US
dc.titleMachine learning algorithms for URLs classification
dc.typeConference Object

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