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Video Steganalysis Based on Intra Prediction Mode Calibration

机译:基于帧内预测模式校准的视频隐分

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Currently, some H.264 video steganographic algorithms based on intra prediction mode (IPM) have been proposed. By modulating IPMs over blocks during the intra-coding process, they achieve low computational complexity, considerable capacity and high security. Up to now, there is no existing steganalytic methods found for effective detection. However, we have observed that the existing IPM-based steganography usually modifies IPMs with non-optimal selection rules which violate the encoding principles. By exploiting these weaknesses, we propose a calibration-based video steganalytic scheme, which extracts IPM calibration (IPMC) features to detect IPM-based steganography. The proposed features are of a very low dimension and sensitive to the presences of non-optimal IPMs. Particularly, calibration parameters are directly obtained from the video stream. Therefore, we avoid estimating erroneous calibration parameters which can lead to the decline of detection performance. Experimental results demonstrate that the proposed IPMC features can be used to effectively detect the IPM modulations even at a low embedding rate, and the IPMC makes the new steganalytic scheme outperform the existing ones.
机译:目前,已经提出了一些基于帧内预测模式(IPM)的H.264视频隐算法。通过在编码过程中调制IPMS上的块,它们实现了低计算复杂性,相当大的容量和高安全性。到目前为止,发现没有发现有效检测的现有落物方法。但是,我们观察到,现有的基于IPM的隐写术通常会使用违反编码原则的非最佳选择规则修改IPM。通过利用这些弱点,我们提出了一种基于校准的视频落地方案,提取IPM校准(IPMC)功能来检测基于IPM的隐写术。所提出的特征是非常低的维度,对非最优IPM的差异敏感。特别地,从视频流直接获得校准参数。因此,我们避免估计可能导致检测性能下降的错误校准参数。实验结果表明,所提出的IPMC特征即使在低嵌入率下也可用于有效地检测IPM调制,并且IPMC使新的STEG分析方案优于现有的。

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