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The Science and Information (SAI) Organization publishes open-access peer-reviewed journals in computer science and artificial intelligence.

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Research Article | Open Access |

Efficient Arnold and Singular Value Decomposition based Chaotic Image Encryption

Author 1: Ashraf Afifi
International Journal of Advanced Computer Science and Applications (IJACSA) · Vol. 10, No. 3 · Published 2019

DOI: https://doi.org/10.14569/IJACSA.2019.0100358

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Abstract

This paper proposes an efficient image encryption that is based on Arnold transform (AT) and the Singular value decomposition (SVD). The proposed method employs AT on a plain image to transpose all image pixels in the positions, then a diffusion process is applied to the resulted encrypted image via SVD decomposing into three segments. The decryption process aims to derive the plain image from the cipher image. Matlab simulation experiments are done to examine the suggested method. The achieved results show the superiority of the suggested approach with respect to encryption quality.

Keywords

Encryption arnold transform singular value decomposition chaotic image encryption

How to Cite this Article

Afifi, A. (2019). Efficient Arnold and Singular Value Decomposition based Chaotic Image Encryption. International Journal of Advanced Computer Science and Applications, 10(3). https://doi.org/10.14569/IJACSA.2019.0100358

Afifi, Ashraf. "Efficient Arnold and Singular Value Decomposition based Chaotic Image Encryption." International Journal of Advanced Computer Science and Applications, vol. 10, no. 3, 2019, https://doi.org/10.14569/IJACSA.2019.0100358.

@article{Afifi2019,
  title     = {Efficient Arnold and Singular Value Decomposition based Chaotic Image Encryption},
  journal   = {International Journal of Advanced Computer Science and Applications},
  volume    = {10},
  number    = {3},
  year      = {2019},
  publisher = {The Science and Information Organization},
  author    = {Ashraf Afifi},
  doi       = {10.14569/IJACSA.2019.0100358},
  url       = {https://doi.org/10.14569/IJACSA.2019.0100358}
}

Open Access — licensed under a Creative Commons Attribution 4.0 International License. Unrestricted use, distribution, and reproduction in any medium, even commercially, as long as the original work is properly cited.

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