Quantum image Gray-code and bit-plane scrambling

Zhou, Ri-Gui; Sun, Yiping; Fan, Ping

doi:10.1007/s11128-015-0964-6

Cited by 98 publications

(28 citation statements)

References 27 publications

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“…Without loss of generality, assume > , then from the fact that − , , is a bijective map and − , , ( 0 ) = − , , ( 0 ), we can conclude − , , ( 0 ) = − +1 − , , ( 0 ), namely, 0 = − − , , ( 0 ). This contradicts (22). Therefore, there must exist a positive integer such that − , , ( ) = .…”

Section: Minimum Transformation Period Andmentioning

confidence: 96%

“…Particularly in the application of robust digital watermark, scrambling technique is a very effective method against cropping attack by shuffling watermark image so that the pixels are dispersed in the position space of carrier image. The popular image scrambling methods include Arnold transform [1-3, 10-12, 18], Fibonacci transform [7,10,13,14], Peano-Hilbert space filling curve [19], knight's tour [8,20], Lucas transform [16], magic square transform [9,17], Gray code [21,22], cellular automata [15,[23][24][25], Baker map [4][5][6]26], subaffine transform [27], and sampling technology [28].…”

Section: Introductionmentioning

confidence: 99%

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Local Negative Base Transform and Image Scrambling

Xiong

Zheng

Wang

et al. 2018

Mathematical Problems in Engineering

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Scrambling transform is an important tool for image encryption and hiding. A new class of scrambling algorithms is obtained by exploiting negative integer as the base of number representation to express the natural numbers. Unlike Arnold transform, the proposed scrambling transform is one-dimensional and nonlinear, and an image can be shuffled by using the proposed transform to rearrange the rows and columns of the image separately or to permute the pixels of the image after scanned into a sequence of pixels; it can be also applied to shuffle certain part region of an image. Firstly, the transformation algorithm for converting nonnegative integers in base to the corresponding integers in base − is given in this paper, which is the computational core of scrambling transform and the basis of studying scrambling transform. Then, the three kinds of transforms are introduced, that is, negative base transform (abbreviated as NBT), modular negative base transform (MNBT), and local negative base transform (LNBT) with three parameters, where NBT is an injection and MNBT a surjection and LNBT a bijection. The minimum transform periods of LNBT are calculated for some different values of the three parameters, and the algorithm for calculating the inverse transform of LNBT is given. The image scrambled by LBNT can be recovered by the transform period or the inverse transform. Numerical experiments show that LNBT is an efficient scrambling transform and a strong operation of confusing gray values of pixels in the application of image encryption. Therefore, the proposed transform is a novel tool for information hiding and encryption of two-dimensional image and one-dimensional audio.

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Section: Minimum Transformation Period Andmentioning

confidence: 96%

Section: Introductionmentioning

confidence: 99%

Local Negative Base Transform and Image Scrambling

Xiong

Zheng

Wang

et al. 2018

Mathematical Problems in Engineering

View full text Add to dashboard Cite

show abstract

“…This paper presents a comparative study of some popular cryptographic image scrambling methods like generalized matrix-based scrambling (transformation) [5] using Arnold's transform [1] and Fibonacci transform [27], gray code with bit plane transformation [25], 2D mapping [20], key based row and column shifting [18], [10] and Fu et. al.…”

Section: Introductionmentioning

confidence: 99%

“…A quantum image gray-code and bit-plane scrambling [25], [21] is presented in which bit-plane scrambling is one of the famous image scrambling techniques. It is used as one of the basic steps in many encryption algorithm [26].…”

Section: Introductionmentioning

confidence: 99%

A Comparative study on Cryptographic Image Scrambling

Mondal¹,

Biswas²,

Mandal³

2017

Annals of Computer Science and Information Systems

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Abstract-In the last few decades, a numerous number of image encryption algorithm has been proposed based on scrambling. Scrambling is the most crucial part of confusiondiffusion based encryption techniques. In the current scenario, the scrambling techniques are used without knowing the cryptographic effect, quality and computational complexity. Hence, an comparative study on scrambling techniques (permutation) is required. In this paper, a comparative study has been done on different scrambling techniques like matrix transformation, bit plane scrambling, 2D mapping and key based row and columns shifting techniques. To determine the quality and efficiency of the scrambling techniques, correlation, entropy, computational complexity have been considered. From the test results it was found that matrix based image scrambling applied on Arnold Transform was the best among the considered techniques in terms of correlation.

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“…The feature of quantum parallelism is utilized in quantum image processing to speed up various processing tasks such as quantum image encryption [3][4][5][6][7][8][9][10][11], quantum image steganography [12,13], quantum image watermarking [14] and so on. Quantum image encryption is widely used to assure security in the information hidden into those images [3].…”

mentioning

confidence: 99%

Quantum color image encryption based on multiple discrete chaotic systems

Li¹,

Abd-El-Atty²,

El‐Latif³

et al. 2017

Annals of Computer Science and Information Systems

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Abstract-In this paper, a novel quantum encryption algorithm for color image is proposed based on multiple discrete chaotic systems. The proposed quantum image encryption algorithm utilize the quantum controlled-NOT image generated by chaotic logistic map, asymmetric tent map and logistic Chebyshev map to control the XOR operation in the encryption process. Experiment results and analysis show that the proposed algorithm has high efficiency and security against differential and statistical attacks.

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Quantum image Gray-code and bit-plane scrambling

Cited by 98 publications

References 27 publications

Local Negative Base Transform and Image Scrambling

Local Negative Base Transform and Image Scrambling

A Comparative study on Cryptographic Image Scrambling

Quantum color image encryption based on multiple discrete chaotic systems

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