QR-Based Fake URL Detection System

Overview

The QR-Based Fake URL Detection System is an intelligent tool designed to analyze QR codes, extract URLs, and classify them as either genuine or fake. Using a combination of image processing, feature engineering, and machine learning.

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Workflow

1. User Uploads QR Code Image

   • The user uploads a QR code image via a Vite + React-based frontend.

2. Image Sent to Flask API for Processing

   • The uploaded image is sent to a Flask backend for further processing.

3. QR Code Decoding

   • The Flask API extracts the URL from the QR code using libraries like OpenCV and Pyzbar.

4. URL Analysis

   • Checks if the URL is shortened and resolves it if necessary.
   • Extracts URL features (length, keywords, patterns, etc.) through feature engineering.

5. Prediction

   • A machine learning model (XGBoost classifier) predicts whether the URL is real or fake based on extracted features.

6. Response Generation

   • The system sends the prediction result (in JSON format) to the frontend for user feedback.

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Features

• Frontend:

  • User-friendly interface for uploading QR code images.
  • Built with Vite and React for fast and interactive performance.

• Backend:

  • Flask-based API for processing images and handling predictions.
  • Image decoding powered by OpenCV and Pyzbar.

• Machine Learning:

  • Utilizes an XGBoost classification model to predict URL authenticity.
  • Feature engineering extracts meaningful patterns for accurate predictions.

• Short URL Resolution:

  • Handles shortened URLs by expanding them before analysis.

• JSON Response:

  • Provides structured and concise feedback to the user.

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Technologies Used

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• Frontend: React, Vite, Tailwind CSS
• Backend: Flask, OpenCV, Pyzbar
• Machine Learning: XGBoost
• Feature Engineering: URL pattern analysis, length detection, and keyword extraction
• Data Exchange: RESTful API with JSON responses

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Installation

Prerequisites

• Python 3.8+
• Node.js 16+
• pipenv (for Python dependencies)

Backend Setup

1. Clone the repository:

   git clone https://github.com/yourusername/qr-fake-url-detector.git
   

2.Navigate to the backend folder

cd back

3.Start the Flask API (Verify to install the dependencies

   python server.py

Frontend Setup

1.Navigate to the frontend folder & Install dependencies

  npm install

2.Start the React application

  npm run dev

PREVIEW

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