Novel image encryption algorithm based on self-adaptive diffusion and combined global scrambling
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摘要: 针对现有的基于比特位层面的图像加密算法中,比特位置乱过程中存在的局限性和局部性问题,提出了一种比特位全局置乱的加密算法,即在置乱过程中,位平面的重组及之后的置乱操作均随机进行,整个置乱过程不只局限在某些位平面之内进行,由此达到全局置乱的效果.该加密算法运用了混沌映射系统,可以同时实现像素的置乱和扩散操作;另外,为了增加对明文的敏感性和有效抵抗攻击,加入了位平面的自适应过程,该过程利用图像不同位平面数据之间的异或运算来进一步修改图像数据.经实验表明:该加密算法对明文和密钥非常敏感,可有效抵抗选择明文攻击,且密文图像像素分布均匀,具有良好的图像加密效果.Abstract: In light of the limitations and locality problems of the bit permutation process in existing bit-level encryption algorithms, a novel algorithm for self-adaptive diffusion and combined global scrambling was proposed. In the diffusion phase, the reorganization and subsequent scrambling process of bit planes is performed randomly, so that the scrambling process is not limited to just some bit planes, and we achieve the effect of global scrambling. The algorithm employed several chaotic mapping systems, allowing permutation and diffusion operations to be implemented simultaneously. To increase sensitivity to plain images and effectively resist attacks, the self-adaptive process of bit planes was added, thereby further modifying the original image data based on given rules. Simulation results demonstrate that the proposed scheme is sensitive to plain images and keys, and can resist Chosen-Plaintext Attack effectively. The cipher image has uniform pixel distribution and good image encryption.
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Key words:
- bit-level /
- image encryption /
- global scrambling /
- chaotic map systems /
- self-adaptive
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表 1 不同加密方法的相关性比较
Tab. 1 Correlation comparison between different encryption methods
图像 算法 水平 垂直 对角 Peppers 本文 0.005 06 -0.004 98 -0.004 11 文献[10] 0.096 88 0.002 31 0.011 63 文献[9] 0.003 00 0.005 40 0.006 50 文献[7] 0.000 71 0.002 16 0.014 89 本文 -0.002 71 -0.004 07 0.008 80 Lena 文献[10] 0.003 63 -0.004 52 0.002 08 文献[9] -0.001 9 -0.003 5 0.007 90 Couple 本文 0.000 35 -0.000 84 0.00164 文献[8] 0.002 40 -0.001 50 -0.008 10 Baboon 本文 0.005 15 0.000 30 0.003 13 Sailboat 本文 0.003 63 -0.000 26 -0.007 59 表 2 明文图像和密文图像的熵值
Tab. 2 Information entropy of plain image and cipher image
表 3 灰度均方差
Tab. 3 Gray mean square error
密钥 灰度均方差 $(\widehat {x}_0, S_0, \alpha)$ 10 876.15 $(x_0, \widehat {S}_0, \alpha)$ 10 900.52 $(x_0, S_0, \widehat {\alpha })$ 10 926.79 表 4 NPCR和UACI
Tab. 4 NPCR and UACI performance
图像 NPCR/% UACI/% Peppers 99.588 33.455 Lena 99.616 33.470 Couple 99.615 33.559 Baboon 99.631 33.373 Sailboat 99.600 33.658 -
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