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LFSR Image Encryption System

Table of Contents

Overview

This project implements a web-based image encryption system using cryptographically secure Linear Feedback Shift Register (LFSR) techniques. Users can upload images, configure encryption parameters, and receive encrypted and decrypted versions in real-time.

Architecture

The project follows a client-server architecture with:

  • A core encryption/decryption module
  • Backend API (FastAPI): Handles encryption/decryption operations
  • Frontend UI (Streamlit): Provides user interface for image upload and parameter configuration

Project Structure

LFSR_Image_Encryption_System/
│
├── LFSR_Encryption.py          # Core encryption & decryption logic
│
├── backend/
│   └── app.py                  # FastAPI application
│
├── frontend/
│   └── app.py                  # Streamlit application
│
├── test_images/
│   ├── lena.jpg
│   ├── test2.jpg
│   └── test5.jpg
│
├── notebook/               # Jupyter notebook
│   └── LFSR_Encryption.ipynb
│
└── README.md                   # Project documentation

Features

  • LFSR-based encryption: Implements confusion and diffusion principles for strong image encryption
  • Configurable parameters: Adjustable seed values and tap positions for different security levels
  • Interactive web interface: User-friendly Streamlit frontend
  • Real-time processing: Immediate encryption/decryption visualization
  • Downloadable results: Save encrypted and decrypted images

Setup

  • Clone the Repository

    git clone https://github.com/Abdelrahman-Elshahed/LFSR_Image_Encryption_Project.git

  • Create and activate a virtual environment:

      python -m venv venv
  source venv/bin/activate  # On Windows use: venv\Scripts\activate

  • Set up dependencies

    Install Python dependencies: To install all the required Python packages for the project, run the following command:

    pip install -r requirements.txt

Run with Streamlit Application

  • Start the backend server: 
    cd backend
uvicorn app:app --reload --port 8000
  • Start the frontend (in a new terminal): 
    cd frontend
streamlit run app.py
  • The application will be available at http://localhost:8501.

Image

Image

Image

Usage

  1. Upload an image using the file uploader in the left column
  2. Configure encryption parameters:
  • Seed Value: Initial state for the LFSR (hexadecimal format)
  • Tap Positions: Comma-separated positions for LFSR feedback
  1. Click "Process Image" to encrypt and decrypt
  2. View the encrypted and decrypted images
  3. Download results using the download buttons
  • Recommended Parameters Seed Values:
  • 16-bit LFSR: 0xACE1
  • 32-bit LFSR: 0xB7E15163
  • 64-bit LFSR: 0x3A7D95C2F168B4E0

Tap Positions:

  • 16-bit LFSR: 16,15,13,4
  • 32-bit LFSR: 32,22,2,1
  • 64-bit LFSR: 64,63,61,60

Technical Implementation

Encryption Process

  1. Confusion Layer:
  • Generates a keystream using LFSR
  • Applies XOR operation between image pixels and keystream
  1. Diffusion Layer:
  • Permutes pixel positions using Fisher-Yates shuffle
  • Uses LFSR values for randomization

Decryption Process

  1. Reverse Diffusion:
  • Applies inverse permutation using stored indices
  1. Reverse Confusion:
  • Applies XOR with the same keystream (XOR is its own inverse)