Phishing Detection 🔍🛡️

A machine learning-based solution designed to detect phishing websites with high accuracy. This project leverages various features and algorithms to identify malicious URLs and protect users from online threats

Features 🚀

• URL Analysis: Examines multiple aspects of URLs to identify phishing patterns

• Machine Learning Models: Implements various algorithms including:

  • Random Forest
  • Support Vector Machines (SVM)
  • Gradient Boosting
  • Neural Networks

• Feature Extraction: Analyzes URL structure, domain information, and content features

• Real-time Prediction: Using our Chrome Extension "PhishGuard" which uses the Google Safe Browsing API to warn about malicious websites

Setup Instructions 💻

1. Clone the repository:

git clone https://github.com/arry-codes/phishing-detection.git
cd phishing-detection

2. Install required dependencies:

pip install -r requirements.txt

3. Run the file app.py

Dataset

The model is trained on a comprehensive dataset containing:

• Legitimate websites from Alexa top sites
• Known phishing URLs from PhishTank and other sources
• Various URL and content-based features

Results

Our best performing model achieves:

• Accuracy: 98.7%
• Precision: 97.2%
• Recall: 96.8%
• F1-Score: 97.0%

Interface 🌐

Chrome Extension 🛠️