Imagine hiding a secret message inside the high-frequency details of an image, transmitting it, and then extracting that exact message without ever needing to share a secret decryption key.
In this article, I will walk through my implementation of a research-backed architecture that uses Convolutional Neural Networks (CNNs) to decode Spread Spectrum Image Steganography (SSIS), bridging the gap between digital signal processing and deep learning. 🧩
This work is an implementation and exploration of the following research paper:
"Secure Spread Spectrum Image Steganography Using a CNN-Based Learned Detector"
Authors: Hossein Fami Tafreshi, Emmanuel Papadakis, and George Baryannis
