TASDF-Stega: High Capacity Secure Text-Audio Joint Steganography Using Diffusion Latent Space

Provably secure steganography ensures indistinguishability between stego and cover carrier through mathematical proofs. However, existing methods face limited embedding capacity and distribution synchronization challenges, especially at high embedding rates. To address these issues, we propose TASDF-Stega, a text-audio joint steganography method based on the latent space of diffusion models, which achieves high capacity and provable security. First, we design an encrypted steganographic mapping module with adaptive arithmetic decoding, which efficiently embeds secret information into the latent space while preserving the distribution. Second, a reversible secret diffusion mechanism enables high-capacity embedding and precise extraction. Moreover, to resolve the problem of distribution parameter synchronization in practical communication, we introduce an audio-assisted joint encode module. This design ensures accurate reconstruction of the diffusion inverse process and avoids cumulative extraction errors. Experimental results on multiple datasets demonstrate that TASDF-Stega achieves provable security, the outperforms state-of-the-art methods in embedding capacity and imperceptibility.