A new set of image encryption algorithms based on discrete orthogonal moments and Chaos theory

2020 ◽  
Vol 79 (27-28) ◽  
pp. 20263-20279 ◽  
Author(s):  
Abdelhalim Kamrani ◽  
Khalid Zenkouar ◽  
Said Najah
Entropy ◽  
2019 ◽  
Vol 21 (1) ◽  
pp. 44 ◽  
Author(s):  
Sameh Askar ◽  
Abdel Karawia ◽  
Abdulrahman Al-Khedhairi ◽  
Fatemah Al-Ammar

In the literature, there are many image encryption algorithms that have been constructed based on different chaotic maps. However, those algorithms do well in the cryptographic process, but still, some developments need to be made in order to enhance the security level supported by them. This paper introduces a new cryptographic algorithm that depends on a logistic and two-dimensional chaotic economic map. The robustness of the introduced algorithm is shown by implementing it on several types of images. The implementation of the algorithm and its security are partially analyzed using some statistical analyses such as sensitivity to the key space, pixels correlation, the entropy process, and contrast analysis. The results given in this paper and the comparisons performed have led us to decide that the introduced algorithm is characterized by a large space of key security, sensitivity to the secret key, few coefficients of correlation, a high contrast, and accepted information of entropy. In addition, the results obtained in experiments show that our proposed algorithm resists statistical, differential, brute-force, and noise attacks.


2019 ◽  
Vol 38 (8) ◽  
pp. 3715-3742 ◽  
Author(s):  
Hicham Karmouni ◽  
Tarik Jahid ◽  
Mhamed Sayyouri ◽  
Abdeslam Hmimid ◽  
Hassan Qjidaa

2014 ◽  
Vol 24 (2) ◽  
pp. 417-428 ◽  
Author(s):  
Haiyong Wu ◽  
Senlin Yan

Abstract This paper presents a new set of bivariate discrete orthogonal moments which are based on bivariate Hahn polynomials with non-separable basis. The polynomials are scaled to ensure numerical stability. Their computational aspects are discussed in detail. The principle of parameter selection is established by analyzing several plots of polynomials with different kinds of parameters. Appropriate parameters of binary images and a grayscale image are obtained through experimental results. The performance of the proposed moments in describing images is investigated through several image reconstruction experiments, including noisy and noise-free conditions. Comparisons with existing discrete orthogonal moments are also presented. The experimental results show that the proposed moments outperform slightly separable Hahn moments for higher orders.


2017 ◽  
Vol 71 ◽  
pp. 264-277 ◽  
Author(s):  
Imad Batioua ◽  
Rachid Benouini ◽  
Khalid Zenkouar ◽  
Azeddine Zahi ◽  
El Fadili Hakim

2019 ◽  
Vol 29 (09) ◽  
pp. 1950115 ◽  
Author(s):  
Guangfeng Cheng ◽  
Chunhua Wang ◽  
Hua Chen

In recent years, scholars studied and proposed some secure color image encryption algorithms. However, the majority of the published algorithms encrypted red, green and blue (called [Formula: see text], [Formula: see text], [Formula: see text] for short) components independently. In the paper, we propose a color image encryption scheme based on hyperchaotic system and permutation-diffusion architecture. The encryption algorithm utilizes a block permutation which is realized by mixing [Formula: see text], [Formula: see text], [Formula: see text] components to strengthen the dependence of each component. Besides, it can reduce time consumption. Then, the key streams generated by the hyperchaotic system are exploited to diffuse the pixels, the three components affect each other again. And in the diffusion process, we can get two totally different encrypted images even though we change the last pixel because the [Formula: see text] component is diffused in reverse order. The experimental results reveal that our algorithm possesses better abilities of resisting statistical attacks and differential attacks, larger key space, closer information entropy to 8, and faster encryption speed compared with other chaos-based color image encryption algorithms.


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