基于关联网络模型的H.264/AVC运动矢量调制信息隐藏检测方法

Steganalysis of Motion Vector-Based Steganography in H.264/AVC by Correlation Network Model

H.264/AVC运动矢量信息隐藏方法具有较大的嵌入容量,同时对重建帧的视频质量引入的附加失真较小,是一种重要的H.264/AVC视频信息隐藏方法.针对该种信息隐藏方法提出了一种隐写分析方法.由于视频帧中物体的完整性和物体在帧间运动的连续性,H.264/AVC时域及空域中相邻编码宏块的运动矢量存在一定的相关性.据此,建立了用于运动矢量隐写分析的时空相邻宏块运动矢量关联网络模型.通过对关联网络进行剪枝得到强相关网络,并对强相关网络中顶点之间的相关性进行了量化表示,从而提取了用于隐写分析的特征向量,结合支持向量机(support vector machine,SVM)构建了隐写检测器.实验表明,与现有的隐写分析算法相比,该文方法具有更好的检测性能,检测准确率均超过90%.

Motion vector modulated steganographic approach is an important type of information hiding method in H.264/AVC video streams,due to its large embedding capacity and low additional distortion induced in reconstructed video frames.In this paper,a novel video steganalysis algorithm is proposed for this type of information hiding method.Firstly,this paper designs a correlation network model to illustrate the correlation between temporal and spatial adjacent motion vectors.Secondly,we obtain a strong correlation network model by simplifying the original correlation network model through a pruning process,accordingly,the quantitative feature vectors of the strong model can be represented through quantifying the correlation of vertexes for steganalysis purpose.Finally,a steganographic detector based on the extracted feature vectors is built by using the support vector machine(SVM).Experiment results show that the proposed algorithm achieves a satisfying performance with the detection accuracy of more than 90%.