5D Hyperchaotic Image Encryption Scheme Based on Fibonacci Q-Matrix

IF 1.7 4区 工程技术 Q2 MATHEMATICS, INTERDISCIPLINARY APPLICATIONS
Complexity Pub Date : 2024-06-28 DOI:10.1155/2024/5437722
Geeta Biban, Renu Chugh, Anju Panwar, Mohammad Sajid
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引用次数: 0

Abstract

This article proposed an image encryption scheme along a novel five-dimensional hyperchaotic system and a Fibonacci Q-matrix (FQ-matrix) for gray images. This designed algorithm follows two key stages: the confusion stage and the diffusion stage. In the confusion step and diffusion step, the placement of the plain image pixels is replaced by a 5D hyperchaotic map and pixel values are changed using the FQ-matrix, respectively. The fortitude of the designed encryption scheme is concluded by countering the algorithm on statistical analysis like histogram analysis, chi-square test, correlation coefficient analysis, information entropy analysis, differential attacks (NPCR, UACI), and NIST suite test. The produced algorithm’s experimental evaluation indicates that the entropy, NPCR, and UACI values tend to be ideal values. The numerous analyses indicate that the proposed algorithm has a lot of characteristics like the low correlation of adjacent cipher pixels, strong security, and large key space, which can give high confidentiality in image data.

Abstract Image

基于斐波那契 Q 矩阵的 5D 超混沌图像加密方案
本文提出了一种基于新型五维超混沌系统和斐波那契 Q 矩阵(FQ 矩阵)的灰度图像加密方案。所设计的算法分为两个关键阶段:混淆阶段和扩散阶段。在混淆阶段和扩散阶段,普通图像像素的位置分别由 5D 超混沌图和利用 FQ 矩阵改变像素值来替代。通过对算法进行直方图分析、卡方检验、相关系数分析、信息熵分析、差分攻击(NPCR、UACI)和 NIST 套件测试等统计分析,得出了所设计加密方案的坚固性。所生成算法的实验评估表明,熵、NPCR 和 UACI 值趋于理想值。大量的分析表明,所提出的算法具有相邻密码像素相关性低、安全性强、密钥空间大等特点,可以为图像数据提供很高的保密性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Complexity
Complexity 综合性期刊-数学跨学科应用
CiteScore
5.80
自引率
4.30%
发文量
595
审稿时长
>12 weeks
期刊介绍: Complexity is a cross-disciplinary journal focusing on the rapidly expanding science of complex adaptive systems. The purpose of the journal is to advance the science of complexity. Articles may deal with such methodological themes as chaos, genetic algorithms, cellular automata, neural networks, and evolutionary game theory. Papers treating applications in any area of natural science or human endeavor are welcome, and especially encouraged are papers integrating conceptual themes and applications that cross traditional disciplinary boundaries. Complexity is not meant to serve as a forum for speculation and vague analogies between words like “chaos,” “self-organization,” and “emergence” that are often used in completely different ways in science and in daily life.
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