基于压缩感知和超混沌系统的多图像加密算法

为了有效改善传输速率并降低带宽负担, 提出一种基于压缩感知和超混沌系统的多图像加密方案. 首先将多幅原始图像拼接成新的明文图像, 并将部分明文信息与随机正整数结合产生混沌系统初始值, 利用超混沌系统产生的伪随机序列生成加密过程所需的测量矩阵、置乱序列及扩散序列. 其次通过离散小波变换、阈值处理以及并行测量对明文图像进行压缩处理, 有效减少运算数据量, 大大加快运行速率. 最后通过无重复置乱操作和双向加模扩散得到最终的密文图像. 经多个层面的仿真模拟实验, 验证了所提算法能有效抵御剪切攻击, 且具有比较高的安全性.

Multiple-image Encryption Algorithm Based on Compressed Sensing and Hyperchaotic System

To effectively improve the transmission rate and reduce bandwidth burden, this study proposes a multiple-image encryption scheme based on compressed sensing and a hyperchaotic system. Specifically, several original images are spliced into a new plaintext image, and some plaintext information is combined with random positive integers to generate the initial value of the chaotic system. The pseudo-random sequence generated by the hyperchaotic system is utilized to produce the measurement matrix, scrambled sequence, and diffusion sequence the encryption process needs. Then, discrete wavelet transform, thresholding, and parallel measurement are performed to compress the plaintext image, which can effectively reduce the amount of operation data and greatly speed up the operation speed. Finally, the final ciphertext image is obtained by non-repeated scrambling and bidirectional mode-adding diffusion. Multiple levels of simulation experiments verify that the proposed algorithm can effectively resist cropping attacks and offer high security.