UppuluriKalyani / ML-Nexus

ML Nexus is an open-source collection of machine learning projects, covering topics like neural networks, computer vision, and NLP. Whether you're a beginner or expert, contribute, collaborate, and grow together in the world of AI. Join us to shape the future of machine learning!
https://ml-nexus.vercel.app/
MIT License
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Feature request-Malicious URL Detection using NLP #694

Closed Shy029 closed 2 weeks ago

Shy029 commented 2 weeks ago

For the Malicious URL Detection using NLP project, I propose developing a machine learning model to classify URLs as either "good" (benign) or "bad" (malicious) by analyzing their lexical and structural features. Using NLP techniques, we can break down URLs to reveal patterns associated with malicious behavior, such as unusual domain names or suspicious keyword combinations. Applying methods like TF-IDF and n-gram analysis, the model will convert URLs into vectorized formats to enable efficient classification. This tool will provide an automated, accurate solution for distinguishing safe URLs from potential threats.

please assign this to me.

github-actions[bot] commented 2 weeks ago

Thanks for creating the issue in ML-Nexus!πŸŽ‰ Before you start working on your PR, please make sure to:

UppuluriKalyani commented 2 weeks ago

@Shy029 already done by someone

github-actions[bot] commented 2 weeks ago

Hello @Shy029! Your issue #694 has been closed. Thank you for your contribution!