基于离散余弦变换域的块相关性和马尔可夫模型的图像隐写分析

Image Steganalysis Based on Block Correlation and Markov Model in DCT Domain

  • 摘要: 提出高阶统计方法检测JPEG图像隐写.为充分描述图像数据及它们空间位置的相关性,运用了JPEG块内、块间系数间的相关性.使用量化分块DCT系数绝对值之差生成水平、垂直和zigzag方向的块内、块间差分数组,采用马尔可夫过程模拟差分数组,提取二阶统计量——差分数组转移概率矩阵——为隐写分析特征向量.仿真结果证明本文提出的方法的检出率高于已知方法的检出率.

     

    Abstract: A high-order statistical method is proposed to detect JPEG image steganography. In order to describe the correlations between image data and their spatial positions fully, both the intra-block and inter-block correlations among JPEG coefficients are utilized. The intra-block and inter-block difference arrays along horizontal, vertical, and zigzag directions are generated by using the difference between the absolute value of quantized block discrete cosine transform coefficients. Markov process is applied to modeling these difference arrays, and the second order statistics, which are transition probability matrices for all difference arrays, are adopted as feature vectors for steganalysis. The simulation results show that the proposed scheme has higher detecting rates than known schemes.

     

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