A Multilayer Nonlinear Permutation Framework and Its Demonstration in Lightweight Image Encryption.

IF 2.1 3区 物理与天体物理 Q2 PHYSICS, MULTIDISCIPLINARY Entropy Pub Date : 2024-10-21 DOI:10.3390/e26100885
Cemile İnce, Kenan İnce, Davut Hanbay
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Abstract

As information systems become more widespread, data security becomes increasingly important. While traditional encryption methods provide effective protection against unauthorized access, they often struggle with multimedia data like images and videos. This necessitates specialized image encryption approaches. With the rise of mobile and Internet of Things (IoT) devices, lightweight image encryption algorithms are crucial for resource-constrained environments. These algorithms have applications in various domains, including medical imaging and surveillance systems. However, the biggest challenge of lightweight algorithms is balancing strong security with limited hardware resources. This work introduces a novel nonlinear matrix permutation approach applicable to both confusion and diffusion phases in lightweight image encryption. The proposed method utilizes three different chaotic maps in harmony, namely a 2D Zaslavsky map, 1D Chebyshev map, and 1D logistic map, to generate number sequences for permutation and diffusion. Evaluation using various metrics confirms the method's efficiency and its potential as a robust encryption framework. The proposed scheme was tested with 14 color images in the SIPI dataset. This approach achieves high performance by processing each image in just one iteration. The developed scheme offers a significant advantage over its alternatives, with an average NPCR of 99.6122, UACI of 33.4690, and information entropy of 7.9993 for 14 test images, with an average correlation value as low as 0.0006 and a vast key space of 2800. The evaluation results demonstrated that the proposed approach is a viable and effective alternative for lightweight image encryption.

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多层非线性排列框架及其在轻量级图像加密中的演示。
随着信息系统的普及,数据安全变得越来越重要。虽然传统的加密方法能有效防止未经授权的访问,但它们在处理图像和视频等多媒体数据时往往力不从心。这就需要专门的图像加密方法。随着移动和物联网(IoT)设备的兴起,轻量级图像加密算法对于资源有限的环境至关重要。这些算法可应用于医疗成像和监控系统等多个领域。然而,轻量级算法面临的最大挑战是如何在强大的安全性与有限的硬件资源之间取得平衡。这项工作介绍了一种适用于轻量级图像加密中混淆和扩散阶段的新型非线性矩阵置换方法。所提出的方法利用三种不同的混沌图(即二维 Zaslavsky 图、一维 Chebyshev 图和一维 Logistic 图)来生成用于置换和扩散的数字序列。使用各种指标进行的评估证实了该方法的效率及其作为稳健加密框架的潜力。我们使用 SIPI 数据集中的 14 幅彩色图像对所提出的方案进行了测试。这种方法只需迭代一次就能处理每幅图像,从而实现了高性能。与其他方案相比,所开发的方案具有显著优势,14 张测试图像的平均 NPCR 为 99.6122,UACI 为 33.4690,信息熵为 7.9993,平均相关值低至 0.0006,密钥空间为 2800。评估结果表明,所提出的方法是轻量级图像加密的一种可行而有效的替代方案。
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来源期刊
Entropy
Entropy PHYSICS, MULTIDISCIPLINARY-
CiteScore
4.90
自引率
11.10%
发文量
1580
审稿时长
21.05 days
期刊介绍: Entropy (ISSN 1099-4300), an international and interdisciplinary journal of entropy and information studies, publishes reviews, regular research papers and short notes. Our aim is to encourage scientists to publish as much as possible their theoretical and experimental details. There is no restriction on the length of the papers. If there are computation and the experiment, the details must be provided so that the results can be reproduced.
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