Digital Cardan Grille: A Modern Approach for Information Hiding

TL;DR

This paper introduces a modern digital Cardan grille framework utilizing GANs and semantic image inpainting to enhance information hiding by embedding secret messages into images while maintaining visual coherence.

Contribution

It proposes a novel Digital Cardan Grille method that leverages GAN-based semantic inpainting for improved and more natural steganographic image hiding.

Findings

Effective hiding of messages in images verified by experiments

Stego images maintain high visual quality and content consistency

Method outperforms traditional steganography techniques

Abstract

In this paper, a new framework for construction of Cardan grille for information hiding is proposed. Based on the semantic image inpainting technique, the stego image are driven by secret messages directly. A mask called Digital Cardan Grille (DCG) for determining the hidden location is introduced to hide the message. The message is written to the corrupted region that needs to be filled in the corrupted image in advance. Then the corrupted image with secret message is feeded into a Generative Adversarial Network (GAN) for semantic completion. The adversarial game not only reconstruct the corrupted image , but also generate a stego image which contains the logic rationality of image content. The experimental results verify the feasibility of the proposed method.