A robust image encryption scheme using chaotic tent map and cellular automata

Naskar, Prabir Kumar; Bhattacharyya, Surojit; Nandy, Dipta; Chaudhuri, Arnab Ray

doi:10.1007/s11071-020-05625-3

Cited by 94 publications

(27 citation statements)

References 65 publications

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“…ree gray images with different sizes are encrypted 100 times, and the average execution times are listed in Table 7. In comparison to the two earlier proposed algorithms [48,49], our algorithm is faster and can meet the daily needs of secure image transmission.…”

Section: Time Complexity Analysismentioning

confidence: 95%

A Novel Image Encryption Algorithm Based on the Delayed Maps and Permutation-Confusion-Diffusion Architecture

Sun

Zhu

2021

Security and Communication Networks

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To improve the dynamical behaviors of 1D chaotic maps, a new linear-delay-modulation method (LDM) is proposed. Derived from the Sine map, a delayed Sine map (DSM) is proposed based on the LDM. Then, we substitute the Sine map in the SIMM system with DSM and obtained a delayed SIMM system (DSIMM). Its chaotic performance is analyzed through the phase diagram, Lyapunov exponent spectrum, and complexity. The results show that the delayed chaotic map can generate more complex dynamical behaviors and more random sequences. Hence, we apply the two delayed systems to a novel image encryption algorithm with the permutation-confusion-diffusion architecture. Firstly, to permutate the pixel of the image efficiently, the plain-image is scrambled by using a multilayer of the nonlinear index. Secondly, the image is confused by using the chaotic matrix generated with two chaotic sequences, and then, the ciphertext is transformed into a 1D sequence. Finally, to improve the plaintext sensitivity and facilitate key management, we enhance the sensitivity by applying a novel diffusion algorithm instead of using plaintext-related keystream. The diffusion equation contains the sum of undiffused pixels and the operation of cyclic bit-shift. Simulation results for the gray image illustrate the effectiveness of the proposed encryption algorithm.

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Section: Time Complexity Analysismentioning

confidence: 95%

A Novel Image Encryption Algorithm Based on the Delayed Maps and Permutation-Confusion-Diffusion Architecture

Sun

Zhu

2021

Security and Communication Networks

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“…Different techniques such as watermarking (Hosny et al 2018;Hosny et al 2019;Hosny et al 2021a, b), image steganography (Zhou et al 2019;Kadhim et al 2020), and image encryption (Naskar et al 2020) are frequently used for securing digital images. Image encryption technique is based on two main stages: encryption and decryption.…”

Section: Introductionmentioning

confidence: 99%

Novel encryption for color images using fractional-order hyperchaotic system

Hosny

Kamal

Darwish

2022

J Ambient Intell Human Comput

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The fractional-order functions show better performance than their corresponding integer-order functions in various image processing applications. In this paper, the authors propose a novel utilization of fractional-order chaotic systems in color image encryption. The 4D hyperchaotic Chen system of fractional-order combined with the Fibonacci Q-matrix. The proposed encryption algorithm consists of three steps: in step#1, the input image decomposed into the primary color channels, R, G, & B. The confusion and diffusion operations are performed for each channel independently. In step#2, the 4D hyperchaotic Chen system of fractional orders generates random numbers to permit pixel positions. In step#3, we split the permitted image into 2 × 2 blocks where the Fibonacci Q-matrix diffused each of them. Experiments performed where the obtained results ensure the efficiency of the proposed encryption algorithm and its ability to resist attacks.

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“…Technology applied to image encryption includes chaotic systems [1][2][3][4][5][6][7][8], cellular automatons [9][10][11], substitution boxes [12][13][14], DNA encoding [15][16][17][18][19][20], elliptic curves [21][22][23][24], finite-precision error [25], Galois field [26] and quantum computing [27,28]. The chaotic system is most popular in the field of image encryption and is continuously improved, such as symmetric chaotic maps [29] and adaptive chaotic maps [30,31].…”

Section: Introductionmentioning

confidence: 99%

Image Encryption Scheme Based on Multiscale Block Compressed Sensing and Markov Model

Shi

Wang

2021

Entropy

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Many image encryption schemes based on compressed sensing have the problem of poor quality of decrypted images. To deal with this problem, this paper develops an image encryption scheme by multiscale block compressed sensing. The image is decomposed by a three-level wavelet transform, and the sampling rates of coefficient matrices at all levels are calculated according to multiscale block compressed sensing theory and the given compression ratio. The first round of permutation is performed on the internal elements of the coefficient matrices at all levels. Then the coefficient matrix is compressed and combined. The second round of permutation is performed on the combined matrix based on the state transition matrix. Independent diffusion and forward-backward diffusion between pixels are used to obtain the final cipher image. Different sampling rates are set by considering the difference of information between an image’s low- and high-frequency parts. So, the reconstruction quality of the decrypted image is better than that of other schemes, which set one sampling rate on an entire image. The proposed scheme takes full advantage of the randomness of the Markov model and shows an excellent encryption effect to resist various attacks.

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A robust image encryption scheme using chaotic tent map and cellular automata

Cited by 94 publications

References 65 publications

A Novel Image Encryption Algorithm Based on the Delayed Maps and Permutation-Confusion-Diffusion Architecture

A Novel Image Encryption Algorithm Based on the Delayed Maps and Permutation-Confusion-Diffusion Architecture

Novel encryption for color images using fractional-order hyperchaotic system

Image Encryption Scheme Based on Multiscale Block Compressed Sensing and Markov Model

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