Deep Steganography
Neural networks that hide an image within another image, with a second model that extracts the hidden content.
This project explores deep learning-based steganography: hiding information inside other information. Neural networks embed a secret image inside a cover image in a way that remains difficult to detect visually.
Overview
The system uses one model to encode a secret image into a cover image, then another model to recover the hidden image from the encoded result.
How It Works
- Encoding Network - Takes a cover image and a secret image, then produces an encoded image that visually resembles the cover image.
- Decoding Network - Extracts the hidden image from the encoded image.
Applications
- Encrypted message transmission
- Digital watermarking
- Secure communication channels
- Copyright protection