Secure Image Steganography with AES Encryption 🔒

A secure data hiding system that combines AES-256 encryption with LSB steganography to protect sensitive information during transmission.

Features ✨

• Military-grade Encryption 🔐

  • AES-256-CBC with PBKDF2 key derivation
  • Secure password hashing with 100,000 iterations
  • Random salt and IV generation

• Advanced Steganography 🖼️

  • LSB (Least Significant Bit) embedding
  • Automatic capacity calculation
  • Header-based length encoding
  • Multi-image format support (PNG, JPG, JPEG)

• User-friendly Interface 💻

  • Streamlit-based web UI
  • Drag-and-drop functionality
  • Real-time feedback
  • Cross-platform compatibility

Installation ⚙️

1. Clone the repository:

git clone https://github.com/x0lg0n/AICTE-INTERNSHIP-PROJETC.git
cd AICTE-INTERNSHIP-PROJECT

Install dependencies:

pip install -r requirements.txt

Usage 🚀

Start the application:

streamlit run app.py

Encoding Process:

• Upload cover image

• Enter secret message

• Set encryption password

• Download protected image

Encoding Demo

Decoding Process:

• Upload protected image

• Enter decryption password

• View extracted message

Decoding Demo

Technical Architecture 🧠

graph TD
    A[Secret Message] --> B[AES-256 Encryption]
    B --> C[Base64 Encoding]
    C --> D[LSB Steganography]
    D --> E[Protected Image]
    E --> F[Transmission]
    F --> G[LSB Extraction]
    G --> H[Base64 Decoding]
    H --> I[AES-256 Decryption]
    I --> J[Original Message]

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🔧 Key Components

Component	Technology Used	Purpose
🔐 Encryption	AES-256-CBC	Data confidentiality
🔑 Key Derivation	PBKDF2-HMAC-SHA256	Secure password hashing
🖼️ Steganography	LSB Embedding	Data concealment
🎨 Image Processing	OpenCV	Pixel manipulation
🛠️ UI Framework	Streamlit	User interface

Contributors 👥

• Siddhartha Kunwar

License 📄

This project is licensed under the MIT License - see the LICENSE file for details.

Acknowledgments 🙏

• Cryptographic functions powered by pycryptodome

• Image processing handled by OpenCV

• UI components from Streamlit