Spatio-Temporal Rich Model-Based Video Steganalysis on Cross Sections of Motion Vector Planes
Spatio-Temporal Rich Model-Based Video Steganalysis on Cross Sections of Motion Vector Planes
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DOI：
10.1109/tip.2016.2567073
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发表时间：
2016-07-01
影响因子：
10.6
通讯作者：
Sezer, Sakir
中科院分区：
文献类型：
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作者：
Tasdemir, Kasim;Kurugollu, Fatih;Sezer, Sakir
提出了一种基于丰富模型的运动矢量隐写分析方法。所提出的隐写分析方法具有显着优越的上级检测精度比以前的方法，甚至有针对性的。检测精度的提高在于本文介绍的几种新方法。首先，它表明，有一个很强的相关性，不仅在空间上，而且在时间上，相邻MV之间的距离较长。因此，时间MV依赖性以及空间依赖性被用于严格的MV隐写分析。第二，与先前使用的过滤器不同，过滤器针对特定的MV隐写术进行了详细设计，使用了一组不同的过滤器，可以捕获由各种MV隐写术方法引入的畸变。滤波器核的种类和数量都大大超过了以前的核。除此之外，滤波器高达五阶，而以前的方法使用最多二阶滤波器。作为这些的结果，所提出的系统捕获各种去相关在一个广泛的时空范围内，并提供了一个更好的覆盖模型。对最突出的MV隐写分析和隐写方法测试所提出的方法。据作者所知，实验部分是MV隐写分析领域最全面的测试，包括五种隐写和七种隐写分析方法。测试结果表明，该方法产生约20%的检测精度提高低有效载荷和5%，在较高的有效载荷。
A rich model-based motion vector (MV) steganalysis benefiting from both temporal and spatial correlations of MVs is proposed in this paper. The proposed steganalysis method has a substantially superior detection accuracy than the previous methods, even the targeted ones. The improvement in detection accuracy lies in several novel approaches introduced in this paper. First, it is shown that there is a strong correlation, not only spatially but also temporally, among neighbouring MVs for longer distances. Therefore, temporal MV dependency alongside the spatial dependency is utilized for rigorous MV steganalysis. Second, unlike the filters previously used, which were heuristically designed against a specific MV steganography, a diverse set of many filters, which can capture aberrations introduced by various MV steganography methods is used. The variety and also the number of the filter kernels are substantially more than that of used in the previous ones. Besides that, filters up to fifth order are employed whereas the previous methods use at most second order filters. As a result of these, the proposed system captures various decorrelations in a wide spatio-temporal range and provides a better cover model. The proposed method is tested against the most prominent MV steganalysis and steganography methods. To the best knowledge of the authors, the experiments section has the most comprehensive tests in MV steganalysis field, including five stego and seven steganalysis methods. Test results show that the proposed method yields around 20% detection accuracy increase in low payloads and 5% in higher payloads.