基于图像信息熵的随机数可视化表达

Image-entropy-based Visual Expression of Random

为了提高严格受控环境下信息隐写算法的安全性和鲁棒性,基于网络图像大数据提出了一种针对小容量负载的图像零隐写隐秘通信算法.在构建算法所需的完备库时,首先根据网格描述符对图像进行单元熵的提取以形成熵矩阵,然后提取熵矩阵的特征值以降维从而减少计算量,最后根据量化算法将特征值量化为一组随机数以构建完备库.实验结果表明:该算法由于没有改变原始载体图像,所以对于抗击已知原始载体的统计、比对分析和尺度缩放攻击、旋转攻击具有非常好的效果,在尺度缩放和旋转攻击的实验中数据恢复率达到95%以上.在安全级别高、受监控程度严格、容量较小的隐匿通信中,比如对称密码系统密钥的交换,具有重要的应用价值.

In order to improve the security and robustness of information hiding method in strict monitoring environment, based on network image big data, this paper proposed a new covert communication algorithm of image zero steganography for payload with low capacity. When constructing the complete library, the first step was to extract the entropy to form the entropy matrix according to the grid descriptor, and the characteristic values of the entropy matrix were then extracted to reduce the amount of computation. Finally, the characteristic values were quantified as a set of random number to build a complete library according to the quantization algorithm. The experimental results show that in statistical analysis, comparison analysis, dimension scaling attack, and rotation attack, the proposed algorithm can achieve good performance because of its none-modifying on carrier image. Particularly, in the test of dimension scaling attack and rotation attack, the rate of data recovering can be over 95%. The algorithm can be very valuable in high security, strict monitoring, and low capacity covert communication： for example, the key exchange of symmetric encryption system.