基于Markov链安全性的LSB匹配隐写算法

隐秘信息的安全性是隐写算法关注的核心问题之一,设计大容量、高安全性的隐写嵌入算法是隐写方法的研究重点.基于Markov链安全标准,以Markov链散度距离最小作为优化嵌入条件,指导LSB匹配嵌入函数,提出了一种优化LSB匹配隐写算法.实验表明该隐写算法在大容量嵌入的同时,保持了载密图像的二阶统计特性,提高了隐写的安全性.

A Novel Steganographic Algorithm in Spatial Domain Based on Markov Chain Security

One of the core issues in steganographic algorithm design is the security of secret information,and more emphases are put on the design of large-capacity and high-security steganographic algorithms in the research of steganography.A novel LSB steganographic method based on Markov chain security benchmarking is proposed,which optimizes the LSB matching function by minimizing the divergence distance of Markov chain in order to preserve the second-order distribution of stego signal,and achieve statistical security.Experimental results show that the proposed method has high ability to keep statistical security,while large-capacity stego information is embedded.