Multi-Stage Residual Hiding for Image-into-Audio Steganography

TL;DR

This paper introduces a multi-stage residual hiding method for image-into-audio steganography that maintains audio quality while effectively embedding images, using a dual-network framework for encoding and decoding residual errors.

Contribution

The proposed multi-stage residual network framework enables flexible payload control and improved hiding performance in cross-modal image-audio steganography.

Findings

Modifications to audio are imperceptible to human listeners.

Decoded images are highly intelligible.

Framework effectively balances payload capacity and audio fidelity.

Abstract

The widespread application of audio communication technologies has speeded up audio data flowing across the Internet, which made it a popular carrier for covert communication. In this paper, we present a cross-modal steganography method for hiding image content into audio carriers while preserving the perceptual fidelity of the cover audio. In our framework, two multi-stage networks are designed: the first network encodes the decreasing multilevel residual errors inside different audio subsequences with the corresponding stage sub-networks, while the second network decodes the residual errors from the modified carrier with the corresponding stage sub-networks to produce the final revealed results. The multi-stage design of proposed framework not only make the controlling of payload capacity more flexible, but also make hiding easier because of the gradual sparse characteristic of residual errors. Qualitative experiments suggest that modifications to the carrier are unnoticeable by human listeners and that the decoded images are highly intelligible.