Color image encryption scheme based on alternate quantum walk and controlled Rubik’s Cube

Zhao, Jingbo; Zhang, Tian; Jiang, Jianwei; Fang, Tong; Ma, Hongyang

doi:10.1038/s41598-022-18079-x

Cited by 14 publications

(6 citation statements)

References 49 publications

(16 reference statements)

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“…Contrarily, quantum information processing [20]has advanced significantly in recent years. A natural generalization of classical information is quantum information [21][22][23][24][25][26][27]. It is the most precise and comprehensive quantum mechanical account in the world.…”

Section: Introductionmentioning

confidence: 99%

RETRACTED: Cost-sensitive classification algorithm combining the Bayesian algorithm and quantum decision tree

Ji,

Bao,

et al. 2023

Front. Phys.

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This study highlights the drawbacks of current quantum classifiers that limit their efficiency and data processing capabilities in big data environments. The paper proposes a global decision tree paradigm to address these issues, focusing on designing a complete quantum decision tree classification algorithm that is accurate and efficient while also considering classification costs. The proposed method integrates the Bayesian algorithm and the quantum decision tree classification algorithm to handle incremental data. The proposed approach generates a suitable decision tree dynamically based on data objects and cost constraints. To handle incremental data, the Bayesian algorithm and quantum decision tree classification algorithm are integrated, and kernel functions obtained from quantum kernel estimation are added to a linear quantum support vector machine to construct a decision tree classifier using decision directed acyclic networks of quantum support vector machine nodes (QKE). The experimental findings demonstrate the effectiveness and adaptability of the suggested quantum classification technique. In terms of classification accuracy, speed, and practical application impact, the proposed classification approach outperforms the competition, with an accuracy difference from conventional classification algorithms being less than 1%. With improved accuracy and reduced expense as the incremental data increases, the efficiency of the suggested algorithm for incremental data classification is comparable to previous quantum classification algorithms. The proposed global decision tree paradigm addresses the critical issues that need to be resolved by quantum classification methods, such as the inability to process incremental data and the failure to take the cost of categorization into account. By integrating the Bayesian algorithm and the quantum decision tree classification algorithm and using QKE, the proposed method achieves high accuracy and efficiency while maintaining high performance when processing incremental sequences and considering classification costs. Overall, the theoretical and experimental findings demonstrate the effectiveness of the suggested quantum classification technique, which offers a promising solution for handling big data classification tasks that require high accuracy and efficiency.

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Section: Introductionmentioning

confidence: 99%

RETRACTED: Cost-sensitive classification algorithm combining the Bayesian algorithm and quantum decision tree

Ji,

Bao,

et al. 2023

Front. Phys.

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show abstract

“…In 2021, Liu et al further optimized the information entropy and resistance to noise attacks of encrypted images, using Arnold transformation and logistic mapping methods [17]. In 2022, Zhao et al proposed a color image encryption scheme based on Rubik's Cube control and quantum random walk [18]. To sum up, current research in the field of image encryption mainly focuses on evaluation indicators such as the security of the optimization algorithm, computational complexity, and clarity of decrypted images [19][20][21].…”

Section: Introductionmentioning

confidence: 99%

Color image encryption algorithm based on quantum random walk and multiple reset scrambling*

Mou,

Dong

2024

Phys. Scr.

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In order to solve the problems of privacy leakage, data string modification and attack threats in the field of image encryption information security, and at the same time ensure the security, integrity and reliability of image data. In this paper, we introduce a novel hybrid color image encryption scheme that increases the complexity of the key space and provides better data integrity protection by combining quantum random walk and SHA-256 algorithm. At the same time, the three chaotic systems are combined and multiple XOR operations are introduced to effectively scramble the space and pixel levels of the color image. Through a large number of simulation experiments and security analysis, the results show that the scheme has efficient encryption performance, excellent ability to resist attacks and excellent privacy protection ability.

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“…[13]; Yi-Nuo Wang et al [20], Rubik's cube transform Vidhya and Brindha [11]; Abitha and Bharathan [15]; AL-Hashemy and Mehdi [16]; Hegui Zhu et al [17]; Jingbo Zhao et al [21], and so on. In 2015, Yuzhen Li et al took a combination of the zigzag scrambling transform and a 3-D logistic map chaotic structure into consideration and proposed an image encryption scheme, which increased the key space and improved the security of image information compared with the general chaotic encryption Yuzhen Li et al [8].…”

Section: Introductionmentioning

confidence: 99%

Image encryption scheme based on a controlled zigzag transform and bit-level encryption under the quantum walk

Zhang

Wang²

2023

Front. Phys.

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With the rapid development of science and technology and network technology, the study of information security has become a hot spot, and image encryption has potential value in this regard. In this paper, an image encryption scheme based on controlled zigzag transform and bit-level encryption under the quantum walk environment is proposed. First, the parameters of the alternating quantum walk are obtained using the SHA-256 method, and the probability matrix of the quantum distribution on the two-dimensional lattice is obtained by multiple walk measurements; second, the spatial dislocation and bit-level dislocation of the image are realized by performing controlled zigzag dislocation and three-dimensional tesseract-like rotational dislocation on the color image; finally, after preprocessing the probability matrix of the quantum distribution, the matrix is bitwise with the dislocated image to achieve the encryption protection of image information. The effectiveness of the encryption scheme is verified by simulation experiments, and the scheme has a significant encryption effect. Compared with other encryption schemes, this scheme has better key sensitivity and dislocation effect, which provides a new approach to the field of image quantum encryption.

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Color image encryption scheme based on alternate quantum walk and controlled Rubik’s Cube

Cited by 14 publications

References 49 publications

RETRACTED: Cost-sensitive classification algorithm combining the Bayesian algorithm and quantum decision tree

RETRACTED: Cost-sensitive classification algorithm combining the Bayesian algorithm and quantum decision tree

Color image encryption algorithm based on quantum random walk and multiple reset scrambling*

Image encryption scheme based on a controlled zigzag transform and bit-level encryption under the quantum walk

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