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Malicious Url Detection PDF

14 Pages·2022·English
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by ['SANKALP MUKIM 20BDS0128']| 2022| 14 pages| English

About Malicious Url Detection

The document proposes a browser extension that uses machine learning to detect malicious URLs. It analyzes trends in malicious URLs to train models like XGBoost and Random Forest. A backend application uses APIs and Azure App Service to integrate the browser extension and models. The goal is to provide free, lightweight URL protection without the drawbacks of antivirus software. Literature on existing approaches is reviewed, identifying gaps like heavy models and inability to learn new words.

Detailed Information

Author:['SANKALP MUKIM 20BDS0128']
Publication Year:2022
Pages:14
Language:English
Format:PDF
Price:FREE
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