Bot Prediction using Mouse Pattern

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.

Folder Structure

• 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.

Features

• 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.

Installation and Setup

1. Clone the repository:

   git clone https://github.com/devvv17i/sih_bot.git
   cd sih_bot

2. Start frontend

   cd frontend2
   npm i
   npm run dev

3. Start the backend

   cd backend
   npm i
   npm start

4. Start the flask server

   cd flask_backend
   pip install -r req.txt
   python server.py