Adaptive steganalysis against WOW embedding algorithm
Adaptive steganalysis against WOW embedding algorithm
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DOI：
10.1145/2600918.2600935
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发表时间：
2014-06
期刊：
影响因子：
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通讯作者：
Weixuan Tang;Haodong Li;Weiqi Luo;Jiwu Huang
中科院分区：
文献类型：
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作者：
Weixuan Tang;Haodong Li;Weiqi Luo;Jiwu Huang
WOW（Wavelet Obtained Weights）[5]是一种先进的空域隐写方法，它可以根据图像的纹理复杂度自适应地将秘密信息嵌入到图像中。通常，图像区域越复杂，其内的像素值将被修改得越多。通过这种方式，它可以实现良好的视觉质量的隐写和高安全性对典型的隐写分析检测器。然而，基于我们的分析，我们指出了在WOW嵌入算法的局限性之一，即，它是很容易缩小这些可能的修改区域为一个给定的隐写图像的基础上，在WOW中使用的嵌入成本。如果我们只是从这些区域提取特征并对它们进行分析，则与从整个图像中提取隐写分析特征相比，检测性能将得到改善。在本文中，我们首先提出了一个自适应的隐写分析方案的WOW方法，并使用空间丰富模型（SRM）为基础的功能[4]，在我们的实验中，这些可能的修改区域建模。在10，000幅图像上的实验结果表明了该方案的有效性。还应注意，我们的隐写分析策略可以与其他隐写分析功能相结合，以检测WOW和/或其他自适应隐写方法在空间和JPEG域。
WOW (Wavelet Obtained Weights) [5] is one of the advanced steganographic methods in spatial domain, which can adaptively embed secret message into cover image according to textural complexity. Usually, the more complex of an image region, the more pixel values within it would be modified. In such a way, it can achieve good visual quality of the resulting stegos and high security against typical steganalytic detectors. Based on our analysis, however, we point out one of the limitations in the WOW embedding algorithm, namely, it is easy to narrow down those possible modified regions for a given stego image based on the embedding costs used in WOW. If we just extract features from such regions and perform analysis on them, it is expected that the detection performance would be improved compared with that of extracting steganalytic features from the whole image. In this paper, we first proposed an adaptive steganalytic scheme for the WOW method, and use the spatial rich model (SRM) based features [4] to model those possible modified regions in our experiments. The experimental results evaluated on 10,000 images have shown the effectiveness of our scheme. It is also noted that our steganalytic strategy can be combined with other steganalytic features to detect the WOW and/or other adaptive steganographic methods both in the spatial and JPEG domains.