Unlocking Secrets: Multi-Image Steganography with Deep Neural Networks 🔐

Ever sent a hidden message in invisible ink to your friends? Are you intrigued by the idea of cryptic message exchange? How about using images for this exchange?
Steganography is what you need!
It is one of the techniques of encryption and over the years, steganography has been used to encode a lower resolution image into a higher resolution image. But steganography using naive methods, like LSB manipulation, is susceptible to statistical analysis.
Our model extends existing deep learning research for encoding multiple secret images onto a single cover by leveraging convolutional neural networks-based deep learning architectures. DeepSteg allows senders to embed up to three secret images onto a single cover using an encoder network and then have multiple decoder networks to obtain the embedded secrets.

This is a project video for Carnegie Mellon University for 11785 (Introduction to Deep Learning), Spring 2020.