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A novel compressive sensing-based framework for image compression-encryption with S-box

机译:具有S-Box的一种新型压缩感应的图像压缩加密框架

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摘要

In this paper, we find that compressive sensing (CS) with the chaotic measurement matrix has a strong sensitivity to plaintext. Because of the quantification executed after CS. however, the plaintext sensitivity produced by CS may be weakened greatly. Thus, we propose a novel CS-based compression-encryption framework (CS-CEF) using the intrinsic property of CS to provide a strong plaintext sensitivity for the compression-encryption scheme, which takes a low additional computation cost. Meanwhile, a simple and efficient Substitution box (S-box) construction algorithm (SbCA) based on chaos is designed. Compared with the existing S-box construction methods, the simulation results prove that the proposed S-box has stronger cryptographic characteristics. Based on the above works, we develop an efficient and secure image compression-encryption scheme using S-box (CSb-CES) under the proposed CS-CEF. The simulations and security analysis illustrate that the proposed CSb-CES has the higher efficiency and security compared with the several state-of-the-art CS-based compression-encryption schemes.
机译:在本文中,我们发现具有混沌测量矩阵的压缩传感(CS)对明文具有很强的敏感性。由于CS之后执行的量化。然而,CS产生的明文灵敏度可能会大大减弱。因此,我们使用CS的内在属性提出了一种新的CS基压缩加密框架(CS-CEF),为压缩加密方案提供了强烈的明文灵敏度,这采用了低额外的计算成本。同时,设计了基于混沌的简单有效的替代盒(S-Box)施工算法(SBCA)。与现有的S箱施工方法相比,仿真结果证明了所提出的S盒具有更强的密码特性。基于上述作品,我们使用所提出的CS-CEF下的S-Box(CSB-CES)开发一种有效和安全的图像压缩加密方案。模拟和安全分析说明了与若干最先进的基于CS的压缩加密方案相比,所提出的CSB-CE具有更高的效率和安全性。

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