Audio steganography cover enhancement via reinforcement learning
Author:
Publisher
Springer Science and Business Media LLC
Subject
Electrical and Electronic Engineering,Signal Processing
Link
https://link.springer.com/content/pdf/10.1007/s11760-023-02819-1.pdf
Reference19 articles.
1. Tang, W., Li, B., Tan, S., Barni, M., Huang, J.: CNN-based adversarial embedding for image steganography. IEEE Trans. Inf. Forensics Secur. 14(8), 2074–2087 (2019). https://doi.org/10.1109/TIFS.2019.2891237
2. Bernard, S., Pevnỳ, T., Bas, P., Klein, J.: Exploiting adversarial embeddings for better steganography. In: Proceedings of the ACM Workshop on Information Hiding and Multimedia Security, pp. 216– 221 ( 2019)
3. Wu, J., Chen, B., Luo, W., Fang, Y.: Audio steganography based on iterative adversarial attacks against convolutional neural networks. IEEE Trans. Inf. Forensics Secur. 15, 2282–2294 (2020). https://doi.org/10.1109/TIFS.2019.2963764
4. Hayes, J., Danezis, G.: Generating steganographic images via adversarial training. Adv. Neural Inf. Proc. Syst. 30 (2017)
5. Shi, H., Dong, J., Wang, W., Qian, Y., Zhang, X.: Ssgan: secure steganography based on generative adversarial networks. In: Pacific Rim conference on multimedia, Springer, pp. 534– 544 ( 2017)
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