SafeLink Analyzer Using Machine Learning

Phishing remains a significant cyber threat that deceives individuals into accessing fraudulent websites, aiming to steal personal information. This study employs the Multinomial Naive Bayes and Logistic Regression machine learning algorithms to detect phishing URLs. We developed a web application u...

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Bibliographic Details
Published in:International journal for research in applied science and engineering technology 2024-06, Vol.12 (6), p.2200-2202
Main Author: Tyagi, Prachi
Format: Article
Language:English
Online Access:Get full text
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Summary:Phishing remains a significant cyber threat that deceives individuals into accessing fraudulent websites, aiming to steal personal information. This study employs the Multinomial Naive Bayes and Logistic Regression machine learning algorithms to detect phishing URLs. We developed a web application using FastAPI and Python, providing users with a tool to verify the authenticity of URLs. Our findings indicate that these algorithms can effectively distinguish between phishing and legitimate URLs, thereby enhancing cybersecurity
ISSN:2321-9653
2321-9653
DOI:10.22214/ijraset.2024.63459