A GAN-Based Framework for Text Hiding in Audio Files Using Spectral Transform Compression
DOI:
https://doi.org/10.65405/2qgdq029Keywords:
GAN, steganography, text hiding, Spectral Transform, CompressionAbstract
A Generative Adversarial Network (GAN)-based framework is a well-known method for concealing textual information within digital audio signals via spectral-domain embedding. Conventional audio steganography techniques, such as Least Significant Bit (LSB) substitution, are low in robustness to signal processing operations, including compression, filtering, and noise addition. To address these limitations, in this study, we embed text into the spectrogram representation of audio signals by using adversarial learning. Based on this model, it adaptively embeds the message in perceptually insignificant frequency regions, while the discriminator enforces statistical similarity between original and stego audio. This demonstrates high imperceptibility, robustness, and payload capacity compared to traditional methods.
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References
[1] D. Ye, S. Jiang and J. Huang, "Heard More Than Heard: An Audio Steganography Method Based on GAN," arXiv, 2019.
[2] J. Yan et al., "FGAS: Fixed Decoder Network-Based Audio Steganography with Adversarial Perturbation Generation," arXiv, 2025.
[3] "A dynamically interactable framework with dual-channel security: GAN-based speech steganography for concealed dialogues," Knowledge-Based Systems, vol. 330, 2025.
[4] X. Kang, H. Zheng, J. Yang and Y.-Q. Shi, "Approaching Optimal Embedding in Audio Steganography With GAN," ICASSP, 2020.
[5] J. Li, K. Wang and X. Jia, "A Coverless Audio Steganography Based on Generative Adversarial Networks," *Electronics*, vol. 12, no. 5, 2023.
[6] Z. Al Hadad and I. H. Ali, "Survey in Image and Audio Steganography by Using Deep Learning Methods," *J. Kufa Math. Comput.*, vol. 10, no. 2, 2023.
[7] "Steganography in Frequency Domain: Hiding Text through Audio Spectrogram," ISSN 1870-4069, 2025.
[8] W. Zhou, J. Zhou, and S. Yang, "An Imperceptible and Robust Audio Watermarking Algorithm Based on SNGAN," International Joint Conference on Neural Networks (IJCNN), pp. 1–8, 2024.
[9] "Enhancing Audio Steganography Through CGAN-Generated Cover Audio and Adaptive LSB Embedding: A Hybrid Approach," Malaysian Journal of Science Health & Technology (MJoSHT), vol. 12, no. 1, 2026.
[10] "EVA-GAN: Enhanced Various Audio Generation via Scalable Generative Adversarial Networks for Spectral Reconstruction," arXiv preprint arXiv:2402.00892, 2024.
