PySpectra Steganography

PySpectra is a steganography module designed to embed and extract hidden messages within images using Spread Spectrum and LSB (Least Significant Bit) techniques.

Overview

This Python-based steganography tool offers functionalities to embed secret messages within image files while preserving the visual integrity of the image. It utilizes Spread Spectrum and LSB methods to encode and decode messages seamlessly.

Features

Embedding: Conceal messages within image files using Spread Spectrum and LSB techniques.
Extraction: Retrieve hidden messages from images while preserving the image's visual quality.
Analysis: Conduct analysis on the image to measure PSNR (Peak Signal-to-Noise Ratio) and SSIM (Structural Similarity Index).

Usage

Embedding: Hide a message within an image.
- Provide the image, message, key, and scalar value.
- Execute the embedding process.
Extraction: Retrieve a hidden message from an image.
- Supply the image and the key used for embedding.
- Extract the concealed message.
Analysis: Evaluate image quality metrics.
- Compare original and modified images.
- Measure PSNR and SSIM values.

Installation

Clone the repository:

git clone https://github.com/snykk/pyspectra-steganography.git

Install the dependecies:
```
pip install -r requirements.txt
```
Run the application:
```
python main.py
```

Contributors

This project is open for contributions and suggestions. If you have an idea for a new feature or a bug fix, don't hesitate to open a pull request

License

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

Result

Cover	Stego	PSNR	SSIM
		73.80361845471792	0.9999518206752678
		80.58434059598379	0.9999988523927771
		76.80170347669058	0.9999982951594725

snykk / pyspectra-steganography

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