{"title":"Malicious URL Detection using Machine Learning","authors":"Prenalee Nanaware","doi":"10.59890/ijist.v2i1.1289","DOIUrl":null,"url":null,"abstract":"\n\n\n\n One of the most prevalent and least protected security risks in existence today is fraudulent websites and URLs.We offer a method that both uses machine learning characteristics to identify phishing URLs and employs text processing techniques to evaluate text and identify incorrect remarks that are suggestive of phishing assaults.\n\n\n\n","PeriodicalId":503863,"journal":{"name":"International Journal of Integrated Science and Technology","volume":"57 ","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2024-01-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Journal of Integrated Science and Technology","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.59890/ijist.v2i1.1289","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
One of the most prevalent and least protected security risks in existence today is fraudulent websites and URLs.We offer a method that both uses machine learning characteristics to identify phishing URLs and employs text processing techniques to evaluate text and identify incorrect remarks that are suggestive of phishing assaults.
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