LFSR Image Encryption System

Table of Contents

• Overview
• Architecture
• Project Structure
• Features
• Setup
• Run with Streamlit Application
• Usage
• Technical Implementation

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.

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

3. Click "Process Image" to encrypt and decrypt
4. View the encrypted and decrypted images
5. 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

2. 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

2. Reverse Confusion:

• Applies XOR with the same keystream (XOR is its own inverse)