Abstract Most current image encryption algorithms encrypt plain images directly into meaningless cipher images. Visually, a few of them are vulnerable to illegal attacks on a few sharing platforms or open channels when being transmitted. Therefore, this paper proposes a new meaningful image encryption algorithm based on compressive sensing and information hiding technology, which hides the existence of the plain image and reduces the possibility of being attacked. Firstly, the discrete wavelet transform (DWT) is employed to sparse the plain image. This is followed by confusion operation on pixel positions, where logistic-tent map is employed to produce a confusion sequence. And then the image is compressed and encrypted by compressive sensing to form an intermediate cipher image. Here, measurement matrix is generated using low-dimension complex tent-sine system. To further enhance recovery quality, we suggest that the intermediate cipher image be filled with random numbers according to the compression ratio and confusing them to obtain the secret image. Finally, two-dimensional (2D) DWT of the carrier image is performed, followed by singular value decomposition. The singular values of the secret image are embedded into the singular values of the carrier image with certain embedding strength to obtain the final visually meaningful encrypted image.

中文翻译：

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基于压缩感知和随机数插入的图像加密与隐藏算法

摘要 目前的图像加密算法大多是将普通图像直接加密为无意义的密码图像。从视觉上看，其中一些在传输时容易受到少数共享平台或开放渠道的非法攻击。因此，本文提出了一种基于压缩感知和信息隐藏技术的新的有意义的图像加密算法，隐藏了普通图像的存在，降低了被攻击的可能性。首先，采用离散小波变换（DWT）对普通图像进行稀疏处理。接下来是对像素位置的混淆操作，其中使用逻辑帐篷地图来产生混淆序列。然后通过压缩感知对图像进行压缩和加密，形成中间密码图像。这里，测量矩阵是使用低维复杂的帐篷正弦系统生成的。为了进一步提高恢复质量，我们建议在中间密码图像中根据压缩率填充随机数并混淆它们以获得秘密图像。最后，对载体图像进行二维 (2D) DWT，然后进行奇异值分解。将秘密图像的奇异值以一定的嵌入强度嵌入到载体图像的奇异值中，得到最终具有视觉意义的加密图像。其次是奇异值分解。将秘密图像的奇异值以一定的嵌入强度嵌入到载体图像的奇异值中，得到最终具有视觉意义的加密图像。其次是奇异值分解。将秘密图像的奇异值以一定的嵌入强度嵌入到载体图像的奇异值中，得到最终具有视觉意义的加密图像。