This project is designed to predict bot activity using mouse movement patterns captured in real-time. It consists of three main components: a frontend built with React and Vite, a Flask backend for data processing and machine learning model training, and a Node.js backend for real-time data collection.
- frontend: Contains the React application used for user interaction and real-time data visualization.
- flask-backend: Includes the Flask server responsible for data processing, model training, and bot prediction.
- nodejs-backend: Houses the Node.js server that collects real-time mouse movement data from the frontend.
- Real-time Mouse Pattern Analysis: Captures and analyzes mouse movement data to detect patterns indicative of bot behavior.
- Machine Learning Model: Utilizes machine learning algorithms to train models based on historical mouse movement patterns and predict bot activities.
- Interactive Visualization: Provides interactive visualizations in the frontend to display real-time and historical data insights.
- Scalable Architecture: Uses separate backends for data processing and frontend interaction, ensuring scalability and modularity.
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Clone the repository:
git clone https://github.com/ayushgit12/BotProof cd sih_bot -
Start frontend
cd frontend2 npm i npm run dev -
Start the backend
cd backend npm i npm start -
Start the flask server
cd flask_backend pip install -r req.txt python app.py