提出一种可解释的图像隐写检测方法，能高效识别高嵌入率隐写图像。
On the Possible Detectability of Image-in-Image Steganography
- 基于小波分解后独立分量的前四阶矩构建检测特征
- 八维输入达84.6%准确率，经典方法超99%准确率
- 适合关注隐写安全与可解释检测的科研人员
本文研究了主流图像-图像隐写方案[1, 2, 3, 4, 5]的可检测性。在该范式中，载荷通常为与载体图像同尺寸的图像，导致极高的嵌入率。我们首先证明嵌入过程产生一个可通过独立成分分析识别的混合模式。随后提出一种简单、可解释的隐写分析方法：基于图像小波分解所得独立分量的前四个矩，用于区分载体与隐写成分的分布。实验表明，该方法效率显著，八维输入向量最高可达84.6%准确率。该脆弱性分析得到两点支持：一是使用无密钥提取网络，二是对传统隐写分析方法（如结合SRM与支持向量机）具有极高可检测性，准确率超过99%。
原文摘要 · Abstract (English)
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.
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