A Bijective Image Encryption System Based on Hybrid Chaotic Map Diffusion and DNA Confusion

Elkamchouchi, Dalia H.; Mohamed, Heba G.; Moussa, Karim H.

doi:10.3390/e22020180

Cited by 48 publications

(30 citation statements)

References 51 publications

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“…A comparison has been drawn in the Table 8. One can see that the proposed cryptosystem does better than [10], [15], [27], [51], [57] as far as entropy is considered for the Lena image.…”

Section: Information Entropy Analysismentioning

confidence: 94%

“…and U ACI for the selected images are 99.6027% and 33.4908% respectively which expressly prove that the potential encryption scheme is sufficiently potent to withstand the attacks of N P CR and U ACI which are differential in character. Further Table 10 draws a comparison of the metrics of the proposed scheme for the Lena image with some other algorithms [10], [15], [27], [51], [57]. Clearly, the proposed method has the better values of N P CR and U ACI than [51] and [15], [51], [57] respectively.…”

Section: E Differential Attackmentioning

confidence: 99%

“…The total key space gets calculated to be 10 105 ≈ 2 348 if 10 −15 is assumed to be the computer precision of the platform in which the research work was carried out. We have taken these latest researches [10], [15], [27], [51], [57] on the image cryptography using the chaotic systems and DNA computing for the sake of comparison. Table 3 conducts a comparative analysis of the potential encryption algorithm with the researches we just mentioned.…”

Section: A Key Spacementioning

confidence: 99%

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DNA Strands Level Scrambling Based Color Image Encryption Scheme

et al. 2020

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In the past, many image encryption schemes have been developed through the swapping operations at the different levels of granularity. These levels span bits, Deoxyribonucleic acid (DNA) molecules, pixels, blocks of pixels. In this study, a new scheme for the encryption of color images based on the DNA strands level scrambling (DNASLS) and chaotic system has been proposed. After a color image is input, it is decomposed into the red, green and blue components. After it, these components are merged to form a big single image. Intertwining logistic map (ILM) has been used for the random data which generates three streams of random numbers. These streams have been further manipulated in such a way that nine streams are spawned out of them. One stream out of these nine streams has been used for the generation of a key image. Two streams have been used to DNA-encode the big single image and the key image. Afterwards, the strands of DNA-encoded single image are swapped with each other. Four streams determine the addresses of two DNA encoded pixels for the selection. A yet another stream is being used to select a particular strand from the DNA strands. To create the diffusion effects, an XOR operation has been done between the DNA encoded image after the swapping of strands and the DNA encoded key image. Finally, the last and ninth stream has been used to decode the DNA-encoded pixels into the decimal form. Purely random numbers with no interdependence have been employed in the entire encryption process. The effects of plaintext sensitivity have been achieved through the incorporation of Secure Hash Algorithm-256 or SHA-256 hash codes. In the end, the experiment and the security analysis have been performed. The results of the validation metrics like information entropy(7.9973), average key sensitivity(99.61%) and mean absolute error(84.7158) demonstrate the security, defiance to the number of attacks and a potential for real world application of the proposed image cipher.

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“…A comparison has been drawn in the Table 8. One can see that the proposed cryptosystem does better than [10], [15], [27], [51], [57] as far as entropy is considered for the Lena image.…”

Section: Information Entropy Analysismentioning

confidence: 94%

Section: E Differential Attackmentioning

confidence: 99%

Section: A Key Spacementioning

confidence: 99%

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DNA Strands Level Scrambling Based Color Image Encryption Scheme

et al. 2020

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“…A good image cipher is expected to distribute the pixels of the given image randomly to defy the varied attacks. The concept of local Shannon entropy (LSE) represents a relatively stricter expression of the randomness of the image pixels [55]. For the given image img, if k non-overlapping blocks S 1 , S 2 ,...., S k with T B pixels are selected randomly, then the LSE is defined mathematically as…”

Section: F Local Shannon Entropymentioning

confidence: 99%

On the Image Encryption Algorithm Based on the Chaotic System, DNA Encoding, and Castle

Iqbal

Atif

Khan³

et al. 2021

IEEE Access

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Hundreds of image encryption algorithms have been developed for the security and integrity of images through the combination of DNA computing and chaotic maps. This combination of the two instruments is not sufficient enough to thwart the potential threats from the cryptanalysis community as the literature review suggests. To inject more robustness and security stuff, a novel image encryption scheme has been written in this research by fusing the chaotic system, DNA computing and castle -a chess piece. As the plain image is input, its pixels are shifted to the scrambled image at the randomly chosen pixel addresses. This scrambling has been realized through the routine called Image Scrambler using Castle (ISUC). Castle randomly moves on the hypothetical large chessboard. Pixels taken from the plain image are shifted to the addresses of the scrambled image, where castle lands in each iteration. After the plain image is scrambled, it is DNA encoded. Two mask images are also DNA encoded. Then to throw the diffusion effects in the cipher, DNA Addition and DNA XOR operations between the DNA encoded pixels data and the DNA encoded mask images have been conducted. Next, the pixels data are converted back into their decimal equivalents. Four dimensional chaotic system has been used to get the chaotic vectors. The hash codes given by the SHA-256 function have been used in the cipher to introduce the plaintext sensitivity in its design. We got an information entropy of 7.9974. Simulation carried out through the machine, and the thorough security analyses demonstrate the good security effects, defiance to the varied attacks from the cryptanalysis community, and the bright prospects for some real world application of the proposed image cipher.

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“…One of the dominant trends in encryption techniques is chaos-based encryption [ 15 , 16 , 17 , 18 , 19 , 20 ]. The reason for this dominance is that the chaos-based encryption schemes are highly sensitive to the initial parameters.…”

Section: Introductionmentioning

confidence: 99%

Image Encryption Using Elliptic Curves and Rossby/Drift Wave Triads

Ullah

Hayat

Bustamante

2020

Entropy

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We propose an image encryption scheme based on quasi-resonant Rossby/drift wave triads (related to elliptic surfaces) and Mordell elliptic curves (MECs). By defining a total order on quasi-resonant triads, at a first stage we construct quasi-resonant triads using auxiliary parameters of elliptic surfaces in order to generate pseudo-random numbers. At a second stage, we employ an MEC to construct a dynamic substitution box (S-box) for the plain image. The generated pseudo-random numbers and S-box are used to provide diffusion and confusion, respectively, in the tested image. We test the proposed scheme against well-known attacks by encrypting all gray images taken from the USC-SIPI image database. Our experimental results indicate the high security of the newly developed scheme. Finally, via extensive comparisons we show that the new scheme outperforms other popular schemes.

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A Bijective Image Encryption System Based on Hybrid Chaotic Map Diffusion and DNA Confusion

Cited by 48 publications

References 51 publications

DNA Strands Level Scrambling Based Color Image Encryption Scheme

DNA Strands Level Scrambling Based Color Image Encryption Scheme

On the Image Encryption Algorithm Based on the Chaotic System, DNA Encoding, and Castle

Image Encryption Using Elliptic Curves and Rossby/Drift Wave Triads

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