This paper investigates the detectability of popular imagein-image steganography schemes [1, 2, 3, 4, 5]. In this paradigm, the payload is usually an image of the same size as the Cover image, leading to very high embedding rates. We first show that the embedding yields a mixing process that is easily identifiable by independent component analysis. We then propose a simple, interpretable steganalysis method based on the first four moments of the independent components estimated from the wavelet decomposition of the images, which are used to distinguish between the distributions of Cover and Stego components. Experimental results demonstrate the efficiency of the proposed method, with eight-dimensional input vectors attaining up to 84.6% accuracy. This vulnerability analysis is supported by two other facts: the use of keyless extraction networks and the high detectability w.r.t. classical steganalysis methods, such as the SRM combined with support vector machines, which attains over 99% accuracy.

翻译：本文研究了流行的图像隐写中图像隐写方案[1, 2, 3, 4, 5]的可检测性。在此范式中，有效载荷通常是与载体图像尺寸相同的图像，导致极高的嵌入率。我们首先证明嵌入过程会产生一种易于通过独立分量分析识别的混合过程。随后，我们提出一种基于图像小波分解估计的独立分量前四阶矩的简单、可解释的隐写分析方法，用于区分载体与隐写分量的分布。实验结果表明所提方法的有效性，八维输入向量可达到高达84.6%的检测准确率。此脆弱性分析得到另外两个事实的支持：无密钥提取网络的使用，以及相对于经典隐写分析方法（如SRM结合支持向量机）的高可检测性，后者准确率超过99%。