Pixel-value differencing (PVD) steganography can embed a large quantity of information and effectively resist regular/singular (RS) detection. Recent steganography techniques that are based on PVD have only focused on improving embedding capacity and image quality. In terms of security, PVD steganography has typically only been tested against well-known RS detection analysis or pixel difference histogram attacks. Modified PVD (MPVD) is an improved method that eliminates certain detectable features of PVD, thereby increasing security. State-of-the-art studies in steganalysis have attempted to detect MPVD steganography by using features of the differences between cover images and stego images, and they have generated models to test suspicious images. However, these methods have low accuracy when the embedding capacity is low. In this study, we propose a chi-square goodness-of-fit-based steganalysis technique that can be applied to MPVD steganography. Experimental results demonstrate that the method effectively detects MPVD steganography even when the embedding ratio is low. Furthermore, the accuracy, precision, and implementation of the method are better than those of existing state-of-the-art techniques in detecting data hidden using MPVD steganography. Therefore, the proposed method contributes to the security analysis of PVD-extended steganography.

像素值差异（PVD）隐写术可以嵌入大量信息，并有效抵抗常规/奇异（RS）检测。基于PVD的最新隐写技术仅集中于提高嵌入能力和图像质量。在安全性方面，PVD隐写术通常仅针对著名的RS检测分析或像素差异直方图攻击进行了测试。修改后的PVD（MPVD）是一种改进的方法，它消除了PVD的某些可检测特征，从而提高了安全性。隐写分析的最新研究已尝试通过利用封面图像和隐身图像之间差异的特征来检测MPVD隐写术，并且他们已经建立了测试可疑图像的模型。但是，当嵌入能力低时，这些方法的精度较低。在这项研究中，我们提出了一种基于卡方拟合优度的隐写分析技术，可以将其应用于MPVD隐写术。实验结果表明，即使嵌入率较低，该方法也能有效检测MPVD隐写术。此外，在检测使用MPVD隐写术进行隐藏的数据时，该方法的准确性，精确度和实现方法优于现有的最新技术。因此，所提出的方法有助于PVD扩展隐写术的安全性分析。在检测使用MPVD隐写技术隐藏的数据方面，该方法的实现和实现优于现有的最新技术。因此，所提出的方法有助于PVD扩展隐写术的安全性分析。在检测使用MPVD隐写技术隐藏的数据方面，该方法的实现和实现优于现有的最新技术。因此，所提出的方法有助于PVD扩展隐写术的安全性分析。