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ISSN 2063-5346
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SUSPICIOUS URL DETECTION USING MACHINE LEARNING APPROACHES

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Chandrakala B M, B V Shruti, Sarala D V
» doi: 10.48047/ecb/2023.12.si5.154

Abstract

Malicious URL, a.k.a. malicious site, is a typical and genuine danger to network safety. Vindictive URLs have spontaneous substance (spam, phishing, drive-by downloads, and so on) and bait clueless clients to become casualties of tricks (financial misfortune, burglary of private data, and malware establishment), and cause misfortunes of billions of dollars consistently. It is basic to identify and follow up on such dangers in a convenient way. Customarily, this recognition is done for the most part through the utilization of boycotts. Be that as it may, boycotts can't be thorough, and need the capacity to distinguish recently created malignant URLs. To improve the over-simplification of noxious URL locators, AI methods have been investigated with expanding consideration as of late. This article points to give a thorough review and an underlying comprehension of Malicious URL Detection strategies utilizing AI

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