为了攻击GIF格式图像中的隐秘术，提出了一种基于图像子块“距离和”的隐写分析算法。该算法中首先将距离用一个索引值同子块中其他索引值的差的绝对值表示，由于索引值的差值可正可负，因而将一个“距离和”区分为“正距离和”和“负距离和”2个矢量，考虑到“正距离和”和“负距离和”两者代数和的符号，它们被归类为“主距离和”和“次距离和”；接着采用直方图计算这些量的统计状态，并通过统计邻接“图像子块”的“距离和”共生矩阵来得到32个统计量；然后通过计算这些统计量的“直方图特征函数的块中心”来得到56维特征向量；最后运用支持向量机构造隐写分析算法。实验结果表明，该算法对GIF图像上多种隐秘术的检测性能均胜过传统算法。此外，“图像子块中不同索引值个数”还可用来改进抽取特征向量的方法。

To attack steganographic schemes in graphics interchange format (GIF) images, a steganalytic algorithm was proposed based on sum of distances (SOD) of sub-block. The distance was computed as an absolute value of the difference between one index and other one in a sub-block of an image. The difference between two indices may be positive or negative so that an SOD was further classified into two kinds. Considering the sign of algebraic sum of positive and negative SODs in a sub-block, the two SODs were differentiated as primary and secondary SODs respectively. 32 statistics were computed using these quantities in an image and a 56-dimensional feature vector was obtained. A steganalytic algorithm was designed based on the feature vector and Support vector machine. Experimental results show that the presented algorithm outperforms traditional methods. The number of different indices in a sub-block was utilized to improve the extracting feature vectors techrique.