基于混沌序列加权抽样和排序变换的图像置乱

为增强网络中传输的数字图像信息的安全性,对一类典型的基于混沌排序图像置乱算法——Ye算法进行了研究,给出应用间隔抽样混沌序列置乱图像可以提高混沌排序置乱算法置乱度这一性质,并依据近似熵理论给出其提升的依据.为增加图像置乱算法的密钥空间,结合Shannon加权保密思想,设计了基于加权抽样混沌序列排序图像置乱算法.结果表明,该方法密钥空间大,置乱强度高,抗重构攻击.

Image scrambling algorithm based on chaotic weighted sampling theory and sorting transformation

In order to enhance the security of digital image transmitted by network, Ye's algorithm, a typical image permutation algorithm based on sorting transformation was studied. Chaotic interval sampling sequence was introduced into image permutation algorithm. By doing so, image permutation effect was improved. In order to understand the internal principle of enhancing permutation effect, approximate entropy theory was employed. For enlarging key space, based on chaotic interval sampling and sorting transformation, new image permutation algorithm was designed in which Shannon's weighted sum idea was employed. In key space, permutation strength and security against reconstruction attack, the proposed permutation algorithm outperforms traditional chaotic sorting permutation algorithm.