The development of multimedia and deep learning technology bring new challenges to steganography and steganalysis techniques. Meanwhile, robust steganography, as a class of new techniques aiming to solve the problem of covert communication under lossy channels, has become a new research hotspot in the field of information hiding. To improve the communication reliability and efficiency for current real-time robust steganography methods, a concatenated code, composed of Syndrome–Trellis codes (STC) and cyclic redundancy check (CRC) codes, is proposed in this paper. The enhanced robust adaptive steganography framework proposed is this paper is characterized by a strong error detection capability, high coding efficiency, and low embedding costs. On this basis, three adaptive steganographic methods resisting JPEG compression and detection are proposed. Then, the fault tolerance of the proposed steganography methods is analyzed using the residual model of JPEG compression, thus obtaining the appropriate coding parameters. Experimental results show that the proposed methods have a significantly stronger robustness against compression, and are more difficult to be detected by statistical based steganalytic methods.

中文翻译：

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使用循环冗余校验码提高实时鲁棒自适应隐写术的可靠性和效率

多媒体和深度学习技术的发展给隐写术和隐写分析技术带来了新的挑战。同时，健壮的隐写术作为旨在解决有损信道下的隐蔽通信问题的一类新技术，已成为信息隐藏领域的新研究热点。为了提高当前实时鲁棒隐写术方法的通信可靠性和效率，本文提出了一种由Syndrome-Trellis码（STC）和循环冗余码（CRC）码组成的级联码。本文提出的增强鲁棒自适应隐写术框架具有强大的错误检测能力，较高的编码效率和较低的嵌入成本。在此基础上，提出了三种抗JPEG压缩和检测的自适应隐写方法。然后，利用JPEG压缩的残差模型分析了所提出的隐写方法的容错能力，从而获得了合适的编码参数。实验结果表明，所提出的方法对压缩具有很强的鲁棒性，并且更难以通过基于统计的隐写分析方法进行检测。