A flexible image encryption algorithm based on 3D CTBCS and DNA computing

Ji, Xu; Mou, Jun; Jiang, Hao

doi:10.1007/s11042-021-10764-9

Cited by 7 publications

(16 citation statements)

References 49 publications

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“…The proposed model outperforms [4] in the Cameraman image with a value of 7.9973, as indicated in the table. In Lena, Baboon, Peppers, and White images, it is as excellent as [2]- [5], [7], [8] models with values of 7.9971, 7.9970, 7.9971, and 7.9970, respectively. As seen in the table, the model predicts results that are 0.0001 to 0.0002 better than those anticipated by others.…”

Section: ) Computational and Time Complexity Analysismentioning

confidence: 99%

“…Moreover in 2021, Xu et al [7] presented a model for 2D and 3D images based on a discrete chaotic system. The hash value is first computed using the SHA-256 hash function and then used to alter the discrete system's initial conditions.…”

Section: Related Workmentioning

confidence: 99%

“…Afterwards, Z2 is subtracted from I4 to get I3. I2 is obtained from applying I3 and Y2 to an XOR procedure using Equation (7).…”

Section: ) Decryption In Dna Levelmentioning

confidence: 99%

“…Where 𝐶(𝑖, 𝑗) is the pixel value in encrypted image, 𝑝(𝐶(𝑖, 𝑗)) is the probability of the occurrence of 𝐶(𝑖, 𝑗). The entropy of encrypted image should be near 8 [2], [6], [7].…”

Section: ) Computational and Time Complexity Analysismentioning

confidence: 99%

“…In Table VIII, the proposed model is compared to the models in [2]- [5], [7], [8] on Lena, Cameraman, Baboon, Peppers, Black, and White images in terms of entropy. The proposed model outperforms [4] in the Cameraman image with a value of 7.9973, as indicated in the table.…”

Section: ) Computational and Time Complexity Analysismentioning

confidence: 99%

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Gray-Scale Image Encryption Using DNA Operations

et al. 2022

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Unsecured networks have recently become widely used for the transmission of confidential images. Consequently, cryptography is crucial for ensuring data confidentiality. Developing a key that is resistant to statistical and differential attacks has always been a challenging objective. In this paper, a novel model is proposed to boost image encryption while maintaining key strength. The proposed model adapts MD5 and SHA-256 hash functions to produce a key. It generates four matrices, X, Y, Z, and W, by using a memristor hyperchaotic system. Arnold's transform was applied to the original image once the key was created. The images were then scrambled using five chaotic maps. The image is then DNA-encoded, diffused using three matrices, and finally DNA-decoded. The proposed model was assessed using twelve performance measures on nine popular images. Compared to previous studies, the results of the proposed model indicate a promising improvement in performance. It achieves a better performance by expanding the key space and increasing its sensitivity.

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Section: ) Computational and Time Complexity Analysismentioning

confidence: 99%

Section: Related Workmentioning

confidence: 99%

“…Afterwards, Z2 is subtracted from I4 to get I3. I2 is obtained from applying I3 and Y2 to an XOR procedure using Equation (7).…”

Section: ) Decryption In Dna Levelmentioning

confidence: 99%

Section: ) Computational and Time Complexity Analysismentioning

confidence: 99%

Section: ) Computational and Time Complexity Analysismentioning

confidence: 99%

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Gray-Scale Image Encryption Using DNA Operations

et al. 2022

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A color image encryption and hiding algorithm based on hyperchaotic system and discrete cosine transform

Wang

Sun

et al. 2023

Nonlinear Dyn

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Remote sensing image and multi-type image joint encryption based on NCCS

Wang

Song

2023

Nonlinear Dyn

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In this paper, an algorithm based on the novel Chebyshev chaotic system (NCCS) for remote sensing image encryption and joint encryption of remote sensing images, grayscale images and color images is proposed. In view of the large amount of remote sensing image data, this paper proposes NCCS, which effectively reduces the time complexity of the algorithm and produces a more uniform pseudo-random sequence with better performance. On this basis, the remote sensing image is encrypted, first put each band of the remote sensing image into different channels, to obtain a three-dimensional matrix, the use of 3-D spiral curve to read each side of the three-dimensional matrix one by one, the obtained one-dimensional sequence into the two-dimensional matrix, this method makes each channel produce a certain coupling at the same time also reduces the dimension of the matrix, effectively enhance the effect of chaos. The chaos map is used to scramble the one-dimensional sequences once, and then to scramble between these one-dimensional sequences, and the method of circular left shift is used to diffuse. Because this method is suitable for encryption of images with multiple channels, it can be used not only for remote sensing image encryption, but also for joint encryption of remote sensing, grayscale, and color images. Simulation results and performance analysis show that the proposed method has good safety. Compared to some existing encryption schemes, this method is more widely applicable.

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A flexible image encryption algorithm based on 3D CTBCS and DNA computing

Cited by 7 publications

References 49 publications

Gray-Scale Image Encryption Using DNA Operations

Gray-Scale Image Encryption Using DNA Operations

A color image encryption and hiding algorithm based on hyperchaotic system and discrete cosine transform

Remote sensing image and multi-type image joint encryption based on NCCS

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