基于位平面随机性测试的隐写分析算法

Bit plane randomness tests based steganalysis algorithm

为有效检测图像中是否含有隐秘信息,提出了一种基于位平面随机性测试的隐写分析算法。该算法利用希尔伯特(H ilbert)扫描将图像最低和次低位平面转化为一维的二值序列,并分别对其进行14项随机性测试。利用测试结果组成28维图像特征向量,构造支持向量机分类器实现对载密图像的可靠检测。多次实验证明:该算法对于空域LSB类隐藏算法嵌入信息在0.05 b/p以上的载密图像具有95%以上的检测率,并且对于频域隐写技术F5也是有效的。

Recently as the fast development of steganography technique, the opposite steganalysis technique is becoming more and more difficult. A novel steganalytic technique was presented based on bit plane randomness tests. Two binary sequences were obtained by scanning the seventh and eighth bit planes of the image with Hilbert scan, then the randomness of this two sequences were tested by several randomness tests respectively. The basic idea is that the randomness of the bit planes will differ between a stego-image and a coveri-image. These telltale marks are used to construct a classifier to distinguish between stego and cover images. The experiments show the detection accuracy of the method is higher than 95% to stego images with a embed rate higher than 0.05 bits per pixel, and that the method is effective to some frequency domain steganographic algorithms such as F5.