Double image encryption using 3D Lorenz chaotic system, 2D non-separable linear canonical transform and QR decomposition

Rakheja, Pankaj; Vig, Rekha; Singh, Phool

doi:10.1007/s11082-020-2219-8

Cited by 38 publications

(19 citation statements)

References 62 publications

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“…Figure 4(a) 7.3671 Table 6 shows the information entropies of the plain and encrypted images (Figure 4 Table 7 shows the comparison results between our information entropies and others' in the case of encrypting the same images. The values obtained by our method are closer to 8 than those from EI-Latif [11], Liu [12], Abd-EI-Atty [16], and Rakheja [19]. Although our result is not better than that of Liu [20], the results differ by only 0.0001.…”

Section: E Information Entropy Analysiscontrasting

confidence: 45%

“…Almost all of these methods are designed for traditional digital images, while the encryption of quantum images remains in its infancy. However, as the traditional computer approaches its physical limits, researchers are beginning to study a new computing model, and quantum computers have produced a series of satisfactory encryption results [11][12][13][14][15][16][17][18][19][20][21][22][23][24]. For example, EI-Latif [11] presented an encryption algorithm of quantum medical images.…”

Section: Introductionmentioning

confidence: 99%

“…Abd-EI-Atty [16] proposed an encryption protocol for NEQR images based on one-particle quantum walks on a circle. A Double image encryption using 3D Lorenz chaotic system, 2D nonseparable linear canonical transform and QR decomposition was proposed byRakheja [19]. Liu [20] proposed a quantum image encryption algorithm based on bit-plane permutation and sine logistic map.…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

A Quantum Image Encryption Method Based on DNACNot

Zhou

2020

IEEE Access

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The image is one of the most important means to store information, and is widely used in every aspect of life. However, the characteristics of images enable them to be easily stolen, tampered with, and copied. Researchers have proposed many encryption methods, with most applying only to traditional digital images. There are few encryption methods for quantum images, and quantum image-oriented encryption technology has begun to attract researchers' attention. This study proposes a quantum image encryption method based on DNA Controlled-Not (DNACNot). Based on the quantum image information, encryption parameters are obtained and transferred as part of a chaotic initial key. Two natural DNA sequences are amplified to obtain the DNA coordinate sequence, and a modified chaos game representation is used to modify the DNA coordinate sequence, which is then used to correct the sequence generated by chaos. The resulting sequence is converted to an integer sequence to obtain DNACNot. A controlled-not operation is performed between DNACNot and the quantum image is scrambled by bit-plane to obtain the encrypted image. The encryption method has high security, a good encryption effect, and a large key space. The method can effectively resist exhaustive, statistical, and differential attacks. The algorithm is easy to implement at a low cost. The encryption time of our proposed method is satisfactory, and the method is suitable for real-time encryption. Moreover, the encryption results can be transmitted over the internet and stored in the cloud.

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Section: E Information Entropy Analysiscontrasting

confidence: 45%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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A Quantum Image Encryption Method Based on DNACNot

Zhou

2020

IEEE Access

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“…Compared with 2D medical images, 3D medical volume data contains more information than the former [27]. Traditional encryption methods, such as DES and RSA, have the disadvantages of complex structure, single key and slow encryption speed, which make it difficult to meet the encryption requirements of medical body data with such a large amount of data [28]. In view of the limitations of traditional image encryption and low-dimensional chaotic encryption, this paper proposes an improved perceptive hash method to encrypt watermark information by using Lorenz system to generate hyperchaotic sequence for 3D displacement.…”

Section: Related Work a Lorenz 3d Hyperchaosmentioning

confidence: 99%

“…However, medical images are different from traditional images. In order to ensure the accuracy of diagnosis, doctors usually embed the patient's name, gender, age and other personal privacy information into the medical images, and these images are an important source for doctors to obtain and diagnose the patient's physical disease information [1]- [3], [28]. In the medical field, the quality of medical data used for diagnosis is very strict and no changes to the original data are allowed.…”

Section: Introductionmentioning

confidence: 99%

Robust Watermarking Algorithm for Medical Volume Data in Internet of Medical Things

Liu

et al. 2020

IEEE Access

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The advancement of 5G technology, big data and cloud storage has promoted the rapid development of the Internet of Medical Things (IoMT). Based on the strict security requirements and high level of accuracy required for disease diagnosis and pathological analysis, 3D medical volume data have been created in large numbers. The IoMT facilitates the rapid transfer of medical information and also makes the protection of pathological information and privacy information of patients increasingly prominent. To solve the security problem, a robust zero-watermarking algorithm based on 3D hyperchaos and 3D dualtree complex wavelet transform is proposed according to the selected feature of medical volume data. The feature combines human visual features with improved perceptual hashing techniques. It is a robust and efficient binary sequence. When implementing the proposed algorithm, the watermark is first scrambled with 3D hyperchaos to enhance security. Then, 3D DTCWT-DCT transformation is applied to medical volume data, and the low-frequency coefficients that can represent the features are selected and binarized to generate the secret key to complete the watermark embedding and extraction. Zero embedding and blind extraction ensure that the original medical volume data is not altered in any form, which meets the special requirements for diagnosis. Simulation results show that the algorithm is robust and can effectively resist common attacks and geometric attacks. It used fewer robust features to effectively bound medical volume data and watermark information, saved bandwidth, and satisfied the security of transmission and storage of medical volume data in the Internet of medical things. In particular, compared with state-of-the-art technology, the proposed algorithm improves the average NC value by 46.67% under geometric attacks. INDEX TERMS Hyperchaos, Internet of medical things, medical volume data, robust watermark, 3D-DTCWT-DCT.

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A new image encryption algorithm based on optimized Lorenz chaotic system

Wang

Zhang

2020

Concurrency and Computation

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Summary In this article, an improved Lorenz system was constructed, in the first stage, a nonlinear term in general Lorenz system was replaced by the sum of term of exponential function and term of the square of single variable, then the dynamic characteristics of the improved Lorenz system were analyzed through the analysis on the phase diagrams and its Lyapunov exponents, and it is proved that the new system has good chaotic characteristics. In the second stage, to improve the security and anti‐attack ability of image encryption algorithm, a new image encryption algorithm was proposed based on this improved Lorenz chaotic system, which was used to generate two groups of key sequences which were used in scrambling encryption and alternative encryption. In the scrambling encryption stage, the gray values of image pixels were sorted in ascending order, and combining with the sequence of scrambled encryption key, the pixel position scrambling was realized. In the phase of the pixel value replacement encryption stage, the gray values of the pixels were changed by the method of cipher text feedback. In the third stage, the quantitative analysis of the effect of encryption was carried out by using histogram, information entropy, correlation coefficient of adjacent pixels. The experimental results show that the improved Lorenz formula is a nonlinear chaotic system, the encrypted algorithm based on this chaotic system can effectively resist chosen plaintext attack, in the encrypted image, the grey value shave random‐like distribution behavior and the adjacent pixels have zero correlation. The algorithm has a 299 bit key space and it is very sensitive to the key.

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Double image encryption using 3D Lorenz chaotic system, 2D non-separable linear canonical transform and QR decomposition

Cited by 38 publications

References 62 publications

A Quantum Image Encryption Method Based on DNACNot

A Quantum Image Encryption Method Based on DNACNot

Robust Watermarking Algorithm for Medical Volume Data in Internet of Medical Things

A new image encryption algorithm based on optimized Lorenz chaotic system

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