research-article

Chaotic Block Color Image Encryption Algorithm Using Cellular Automata and DNA Sequence

Authors:

Dingqin LiuAuthors Info & Claims

AIPR '21: Proceedings of the 2021 4th International Conference on Artificial Intelligence and Pattern Recognition

Pages 386 - 392

https://doi.org/10.1145/3488933.3488966

Published: 25 February 2022 Publication History

Abstract

In this paper, a novel chaotic block color image encryption algorithm based on cellular automata and deoxyribonucleic acid (DNA) sequence is proposed. Firstly, the three components of the color image are converted to three DNA matrices by DNA encoding rules and combine into a new matrix. Secondly, divide the new matrix into several unequal blocks and elementary cellular automata (ECA) is introduced to effectively break the correlation of inter-intra components by dynamically swapping all blocks in the new matrix. Finally, double DNA operations are employed to hide the information of the image as much as possible by diffusing three permutated DNA matrices. In addition, a 512-bit plain image hash value and the external keys are introduced to generate the initial value for the chaotic system, which makes the algorithm is sensitive to the plain image. DNA encoding rules rely on plaintext information. Simulation results and security analyses demonstrate that our algorithm has the ability to resist various typical attacks and owns an acceptable running time.

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Cited By

Moya-Albor ERomero-Arellano ABrieva JGomez-Coronel S(2023)Color Image Encryption Algorithm Based on a Chaotic Model Using the Modular Discrete Derivative and Langton’s AntMathematics10.3390/math1110239611:10(2396)Online publication date: 22-May-2023
https://doi.org/10.3390/math11102396

Index Terms

Chaotic Block Color Image Encryption Algorithm Using Cellular Automata and DNA Sequence
1. Hardware
  1. Emerging technologies
    1. Quantum technologies
2. Information systems
  1. Data management systems
    1. Data structures

Index terms have been assigned to the content through auto-classification.

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AIPR '21: Proceedings of the 2021 4th International Conference on Artificial Intelligence and Pattern Recognition

September 2021

715 pages

ISBN:9781450384087

DOI:10.1145/3488933

Copyright © 2021 ACM.

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 25 February 2022

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Natural Science Foundation of Shaanxi Province

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AIPR 2021

AIPR 2021: 2021 4th International Conference on Artificial Intelligence and Pattern Recognition

September 24 - 26, 2021

Xiamen, China

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Cited By

Moya-Albor ERomero-Arellano ABrieva JGomez-Coronel S(2023)Color Image Encryption Algorithm Based on a Chaotic Model Using the Modular Discrete Derivative and Langton’s AntMathematics10.3390/math1110239611:10(2396)Online publication date: 22-May-2023
https://doi.org/10.3390/math11102396

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