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GitHub / 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.

JSON API: http://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/RimTouny%2FPhishing-Attack-Detection-using-Machine-Learning

Stars: 1
Forks: 0
Open issues: 0

License: mit
Language: Jupyter Notebook
Size: 1.72 MB
Dependencies parsed at: Pending

Created at: over 1 year ago
Updated at: over 1 year ago
Pushed at: over 1 year ago
Last synced at: over 1 year ago

Topics: cybersecurity, eda, f1-score, feature-extraction, feature-selection, lazy-classifier, machine-learning, oversampling, phishing-attacks, phishing-detection, phishing-urls, smote, stacking-classifier, true-negative-rate, true-positive-rate, voting-classifier

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