Nonlinear optical multi-image encryption scheme with two-dimensional linear canonical transform

Huang, Zhenghua; Cheng, Shan; Gong, Li-Hua; Zhou, Nanrun

doi:10.1016/j.optlaseng.2019.105821

Cited by 129 publications

(53 citation statements)

References 37 publications

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“…It also provides the necessary image encryption tests for ChaosNet that prove its prototypical cryptographic strength. Such tests are typically used in such scenarios [31], [32]. Initial tests of encryption with ChaosNet are performed on highway traffic images taken from the SERSU [2] are shown in Table 2, where the distinct histograms of the plainimages become unintelligible cipherimages with flat histograms, increasing security.…”

Section: Resultsmentioning

confidence: 99%

Chaotic Encryption Algorithm With Key Controlled Neural Networks for Intelligent Transportation Systems

2019

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The security of sensitive information is vital in many aspects of multimedia applications such as Intelligent Transportation Systems (ITSs), where traffic data collection, analysis and manipulations is essential. In ITS, the images captured by roadside units form the basis of many traffic rerouting and management techniques, and hence, we should take all precautions necessary to deter unwanted traffic actions caused by malicious adversaries. Moreover, the collected traffic images might reveal critical private information. Consequently, this paper presents a new image encryption algorithm, denoted as ChaosNet, using chaotic key controlled neural networks for integration with the roadside units of ITSs. The encryption algorithm is based on the Lorenz chaotic system and the novel key controlled finite field neural network. The obtained cryptanalysis show that the proposed encryption scheme has substantial mixing properties, and thus cryptographic strength with up to 5% increase in information entropy compared to other algorithms. Moreover, it offers consistent resistance to common attacks demonstrated by nearly ideal number of changing pixel rate (NPCR), unified averaged changed intensity (UACI), pixel correlation coefficient values, and robustness to cropped attacks. Furthermore, it has less than 0.002% difference in the NPCR and 0.3% in the UACI metrics for different test images.

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Section: Resultsmentioning

confidence: 99%

Chaotic Encryption Algorithm With Key Controlled Neural Networks for Intelligent Transportation Systems

2019

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“…It is well-known that Shannon has proved that diffusion and confusion are two main performances of a reliable image encryption system: where diffusion means that the pixel value of the original image is altered, and confusion means that the pixel positions are varied in some way to reduce the correlation between neighbor pixels [20]- [23]. Indeed, it can be seen that the operations of confusion and diffusion are extensively considered in image encryption algorithms [24]- [26].…”

Section: Introductionmentioning

confidence: 99%

A Novel Color Image Encryption Algorithm Based on Three-Dimensional Chaotic Maps and Reconstruction Techniques

Qian

Yang

et al. 2021

IEEE Access

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In the paper, a novel color image encryption scheme is proposed by use of the threedimensional chaotic maps and some data reconstruction techniques. In the diffusion process of the encryption algorithm, the three-dimensional chaotic Logistic map is introduced to changes the pixel value of the plain image. Meanwhile, in the confusion process, the three-dimensional chaotic Cat map is applied to deal with the position of the image pixels. Moreover, some data reconstruction techniques are employed for the better encryption result. Furthermore, the corresponding decryption algorithm is also given. The significant advantages of our method are the effectiveness and simplicity, and our proposed method breaks the correlation between image pixel layers, offers a large key space and against differential and statistical attacks effectively. Finally, the superiority of the proposed algorithm will be shown by the experimental results, security analysis, and the corresponding comparisons with literature.

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“…A nonlinear optical multi-image encryption scheme based on chaotic system and two-dimensional linear canonical transform was proposed in [13]. In this method, low-frequency sub-bands of the four grayscale images are extracted with the contourlet transform, and the phase truncation and the bitwise XOR operation, as nonlinear processes, improve the robustness of the presented multi-image encryption scheme against chosen-plaintext attack.…”

Section: Introductionmentioning

confidence: 99%

A novel multi-image cryptosystem based on weighted plain images and using combined chaotic maps

et al. 2021

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This paper introduces a new multi-image cryptosystem based on modified Henon map and nonlinear combination of chaotic seed maps. Based on the degree of correlation between the adjacent pixels of the plain image, a unique weight is assigned to the plain image. First, the coordinates of plain images are disrupted by modified Henon map as confusion phase. In the first step of diffusion phase, the pixels content of images are changed separately by XOR operation between confused images and matrices with suitable nonlinear combination of seed maps sequences. These combination of seed maps are selected depending on the weight of plain images as well as bifurcation properties of mentioned chaotic maps. After concatenating the matrices obtained from the first step of diffusion phase, the bitwise XOR operation is applied between newly developed matrix and the other produced matrix from the chaotic sequences of the Logistic-Tent-Sine hybrid system, as second step of diffusion phase. The encrypted image is obtained after applying shift and exchange operations. The results of the implementation using graphs and histograms show that the proposed scheme, compared to some existing methods, can effectively resist common attacks and can be used as a secure method for encrypting digital images.

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Nonlinear optical multi-image encryption scheme with two-dimensional linear canonical transform

Cited by 129 publications

References 37 publications

Chaotic Encryption Algorithm With Key Controlled Neural Networks for Intelligent Transportation Systems

Chaotic Encryption Algorithm With Key Controlled Neural Networks for Intelligent Transportation Systems

A Novel Color Image Encryption Algorithm Based on Three-Dimensional Chaotic Maps and Reconstruction Techniques

A novel multi-image cryptosystem based on weighted plain images and using combined chaotic maps

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