Image encryption based on a reality-preserving fractional discrete cosine transform and a chaos-based generating sequence

Wu, Jianhua; Guo, Fen; Zeng, Pingping; Zhou, Nanrun

doi:10.1080/09500340.2013.858189

Cited by 24 publications

(10 citation statements)

References 27 publications

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“…In addition, Table . 6 indicates that correlation coefficients of the original images are close to 1, correlation coefficients of the cipher images are close to 0, which further demonstrates that the designed algorithm destroys the correlation between adjacent pixels of original images. In addition, the correlation coefficients of the Couple, Camera, Lake and Boat images are compared with other algorithms [16]- [21], [47], [48] in Table . 7. The results show that the designed algorithm has better encryption effect.…”

Section: F Correlation Of Adjacent Pixelsmentioning

confidence: 99%

“…In general, when the NPCR > N * α , which show that it can prevent differential attack. If the significance level is α, the critical UACI values (U * α −, U * α +) are calculated by -0.0012 0.0095 -0.0093 Algorithm [47] -0.0306 0.3188 -0.0137 Algorithm [48] 0.0600 0.0196 -0.0231 Algorithm [21] 0.2071 0.2128 0.2102 Ours Cipher image "Boat" 0.0065 -0.0031 0.0019 Algorithm [16] 0.0086 0.0060 0.0017 Algorithm [17] 0.0250 0.0186 -0.0051 Algorithm [18] 0.1830 0.1316 0.0599 Algorithm [19] -0.0037 -0.0177 -0.0131…”

Section: G Differential Attacksmentioning

confidence: 99%

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2D-SCMCI Hyperchaotic Map for Image Encryption Algorithm

Sun

2021

IEEE Access

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Chaos has unpredictability and initial condition sensitivity, which known as a best candidate for cryptography application. However, there are many defects for the existing chaotic cryptography systems due to the use of chaotic maps that without complexity dynamic properties. To overcome these weaknesses, this work designed a 2D-SCMCI hyperchaotic map based on Cascade Modulation Couple (CMC) and two 1D-chaotic map. The dynamic characteristics of the 2D-SCMCI hyperchaotic map are analyzed through attractor trajectory, 0-1 test, bifurcation diagram, Lyapunov exponents and spectrum entropy (SE) complexity. The results of analysis indicate that 2D-SCMCI hyperchaotic map has rich dynamic performance and randomness, which illustrates that it is more suitable for image encryption algorithm. Therefore, an image encryption algorithm is proposed by 2D-SCMCI hyperchaotic map. In encryption algorithm, the image is scrambled by row and column, forward and backward diffusion are used to diffuse image pixel values. The security performances analysis results indicate that the introduced algorithm has better security characteristics.

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Section: F Correlation Of Adjacent Pixelsmentioning

confidence: 99%

Section: G Differential Attacksmentioning

confidence: 99%

2D-SCMCI Hyperchaotic Map for Image Encryption Algorithm

Sun

2021

IEEE Access

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“…The reality-preserving fractional discrete cosine transform (RPFrDCT) matrix  C is defined in [13,14]: …”

Section: A Reality-preserving Fractional Discrete Cosine Transformmentioning

confidence: 99%

Color image encryption algorithm with realitypreserving fractional discrete cosine transform and spatiotemporal chaotic mapping

Liang

Liu

2015

Proceedings of 2015 International Conference on Intelligent Computing and Internet of Things

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A color image encryption scheme is proposed based on a reality-preserving fractional discrete cosine transform (RPFrDCT) and spatiotemporal chaotic mapping. The scrambling and diffusion operations are carried out after the RPFrDCT and make three components of image affect each other. The main advantages of this scheme are the real-valued output, the nonlinear manipulation, the high sensitiveness and high robustness to the cipher keys. Experimental results demonstrate that the proposed encryption scheme is feasible and effective.

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“…For example, LANG first implemented a reality-preserving multi-parameter Fourier transform and applied it for image encryption [13]. WU et al [14] proposed an image encryption algorithm based on a reality-preserving fractional discrete cosine transform, in which a real-valued output facilitates efficient storage and transmission. However, these image encryption systems are a linear one which are relatively weak in security in comparison to nonlinear encryption systems.…”

Section: Introductionmentioning

confidence: 99%

Image encryption based on permutation polynomials over finite fields

Wu¹,

Liu²,

Zhu³

2020

Optica Applicata

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In this paper, we propose an image encryption algorithm based on a permutation polynomial over finite fields proposed by the authors. The proposed image encryption process consists of four stages: i) a mapping from pixel gray-levels into finite field, ii) a pre-scrambling of pixels’ positions based on the parameterized permutation polynomial, iii) a symmetric matrix transform over finite fields which completes the operation of diffusion and, iv) a post-scrambling based on the permutation polynomial with different parameters. The parameters used for the polynomial parameterization and for constructing the symmetric matrix are used as cipher keys. Theoretical analysis and simulation demonstrate that the proposed image encryption scheme is feasible with a high efficiency and a strong ability of resisting various common attacks. In addition, there are not any round-off errors in computation over finite fields, thus guaranteeing a strictly lossless image encryption. Due to the intrinsic nonlinearity of permutation polynomials in finite fields, the proposed image encryption system is nonlinear and can resist known-plaintext and chosen-plaintext attacks.

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Image encryption based on a reality-preserving fractional discrete cosine transform and a chaos-based generating sequence

Cited by 24 publications

References 27 publications

2D-SCMCI Hyperchaotic Map for Image Encryption Algorithm

2D-SCMCI Hyperchaotic Map for Image Encryption Algorithm

Color image encryption algorithm with realitypreserving fractional discrete cosine transform and spatiotemporal chaotic mapping

Image encryption based on permutation polynomials over finite fields

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