RimTouny/Phishing-Attack-Detection-using-Machine-Learning

Advancing Cybersecurity with AI: This project fortifies phishing defense using cutting-edge models, trained on a diverse dataset of 737,000 URLs. It was the final project for the AI for Cybersecurity course in my Master's at uOttawa in 2023.

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Experimental

This project helps cybersecurity analysts and IT security professionals automatically identify and flag suspicious website links. By analyzing various characteristics of a URL, it determines if a link is likely a phishing attempt or benign. The output is a clear classification (phishing or safe) for each URL.

No commits in the last 6 months.

Use this if you need a robust way to classify URLs for phishing threats, enhancing your organization's defenses against social engineering attacks.

Not ideal if you're looking for a user-friendly, out-of-the-box application rather than a machine learning model you can integrate.

cybersecurity phishing-detection URL-analysis threat-intelligence network-security
Stale 6m No Package No Dependents
Maintenance 0 / 25
Adoption 6 / 25
Maturity 16 / 25
Community 5 / 25

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1

Language

Jupyter Notebook

License

MIT

Last pushed

Jan 12, 2024

Commits (30d)

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