An Image Encryption Scheme Combining 2D Cascaded Logistic Map and Permutation-Substitution Operations

IF 1.9 Q2 MATHEMATICS, INTERDISCIPLINARY APPLICATIONS
D. Setiadi, Nova Rijati
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引用次数: 2

Abstract

Confusion, diffusion, and encryption keys affect the quality of image encryption. This research proposes combining bit- and pixel-level permutation and substitution methods based on three advanced chaotic logistic map methods. The three chaotic methods are the 2D Logistic-adjusted-Sine map (2D-LASM), the 2D Logistic-sine-coupling map (2D-LSCM), and the 2D Logistic ICMIC cascade map (2D-LICM). The encryption method’s design consists of six stages of encryption, involving permutation operations based on chaotic order, substitution based on modulus and bitXOR, and hash functions. Hash functions are employed to enhance key space and key sensitivity quality. Several testing tools are utilized to assess encryption performance, including histogram and chi-square analysis, information entropy, correlation of adjacent pixels, differential analysis, key sensitivity and key space analysis, data loss and noise attacks, NIST randomness tests, and TestU01. Compared to using a single 2D logistic map, the amalgamation of bit-level and pixel-level encryption and the utilization of three 2D cascade logistic maps has improved encryption security performance. This method successfully passes the NIST, TestU01, and chi-square tests. Furthermore, it outperforms the previous method regarding correlation, information entropy, NPCR, and UACI tests.
一种结合二维级联Logistic映射和置换置换运算的图像加密方案
混淆、扩散和加密密钥会影响图像加密的质量。本研究在三种先进的混沌逻辑图方法的基础上,提出了结合比特和像素级排列和替换方法。这三种混沌方法分别是二维逻辑调整正弦映射(2D-LASM)、二维逻辑正弦耦合映射(2D_LSCM)和二维逻辑ICMIC级联映射(2D-LICM)。加密方法的设计包括六个加密阶段,包括基于混沌顺序的置换运算、基于模数和位XOR的替换以及哈希函数。采用哈希函数来增强密钥空间和密钥敏感度质量。使用多种测试工具来评估加密性能,包括直方图和卡方分析、信息熵、相邻像素的相关性、差分分析、密钥敏感性和密钥空间分析、数据丢失和噪声攻击、NIST随机性测试和TestU01。与使用单个2D逻辑图相比,比特级和像素级加密的融合以及三个2D级联逻辑图的使用提高了加密安全性能。该方法成功通过了NIST、TestU01和卡方测试。此外,它在相关性、信息熵、NPCR和UACI测试方面优于以前的方法。
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来源期刊
Computation
Computation Mathematics-Applied Mathematics
CiteScore
3.50
自引率
4.50%
发文量
201
审稿时长
8 weeks
期刊介绍: Computation a journal of computational science and engineering. Topics: computational biology, including, but not limited to: bioinformatics mathematical modeling, simulation and prediction of nucleic acid (DNA/RNA) and protein sequences, structure and functions mathematical modeling of pathways and genetic interactions neuroscience computation including neural modeling, brain theory and neural networks computational chemistry, including, but not limited to: new theories and methodology including their applications in molecular dynamics computation of electronic structure density functional theory designing and characterization of materials with computation method computation in engineering, including, but not limited to: new theories, methodology and the application of computational fluid dynamics (CFD) optimisation techniques and/or application of optimisation to multidisciplinary systems system identification and reduced order modelling of engineering systems parallel algorithms and high performance computing in engineering.
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