基于KPCA和CS的同步图像压缩和加密

Jinli Cheng, Xiangjun Wu
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引用次数: 0

摘要

介绍了一种基于LSS-CML、压缩感知(CS)和k -主成分分析(KPCA)方法的图像加密算法。首先,使用CS和KPCA方法对原始图像进行压缩,其中利用LSS-CML构造键控伪随机测量矩阵;然后由原始图像和LSS-CML产生的密钥流对压缩图像进行洗牌和扩散。利用原始图像和散列函数SUA-S12对LSS-CML的初始条件和参数进行了更新。因此,密钥流同时依赖于纯图像和LSS-CML,这使得加密方法能够抵抗2选择明文和已知明文攻击。实验结果和性能分析验证了该方案的有效性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Simultaneous Image Compression and Encryption Via KPCA and CS
This paper introduces a novel image encryption algorithm by means of LSS-CML, compressive sensing (CS) and K-Principle Component Analysis (KPCA) method. Firstly, the original image is compressed using CS and the KPCA method, in which LSS-CML is utilized to construct the key-controlled pseudo-random measurement matrices. Then the compressed image is shuffled and diffused by the key streams produced from both the original image and LSS-CML. The initial conditions and parameters of LSS-CML are updated with the help of the original image and the hash function SUA-S12. Thus the key streams rely on both the plain-image and LSS-CML, which make the encryption approach resistance to the 2chosen-plaintext and known-plaintext attacks. Experimental results and performance analysis have verified the validity of the presented scheme.
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