Multiple image encryption algorithm using channel randomization and multiple chaotic maps

Developing robust and secure image encryption methods for transmitting multiple images in batches over unprotected networks has become imperative. This necessity arises from the limitations of single-image encryption techniques in managing the escalating volume of extensive data. This paper introduces a novel three-layer multiple-image encryption (MIE) technique to encrypt batch images based on three 2D-chaotic maps. All multiple-color images are divided into RGB channels in the first layer. The images in each channel go through a randomization process to be arranged at random before being combined to form a single image (batch) used as the input for the following layer. In the second layer, chaotic sequences for scrambling pixels in each channel independently are generated using Baker, Henon, and 2-D Logistic chaotic maps, resulting in a scrambled image. The diffusion process is applied in the final layer by independently changing the values of the pixels in each channel using different chaotic sequences generated from the three maps and the XORing operation. The efficiency of the proposed scheme is validated through key sensitivity, key space analysis, complexity analysis, entropy assessment, and tests, including horizontal, vertical, and diagonal correlation, MSE, PSNR, UACI, and NPCR. Moreover, experimental results and a thorough security analysis affirm that the proposed encryption technique has effectively attained confidentiality and robust resistance against various attacks.

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Publication Details

Journal
Scientific Reports
Published
2024-12-23
DOI
https://doi.org/10.1038/s41598-024-79282-6
Citations
19
Primary Topic
Chaos-based Image/Signal Encryption
Type
article
Field-Weighted Citation Impact
4.73

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article

Multiple image encryption algorithm using channel randomization and multiple chaotic maps

Ahmed M. Elshewey, Khalid Mohamed Hosny, Yasmin M. Elnabawy, Rania A. Salama
19 citations
Scientific Reports
Chaos-based Image/Signal Encryption
4.73
article

Multiple image encryption algorithm using channel randomization and multiple chaotic maps

Ahmed M. Elshewey, Khalid Mohamed Hosny, Yasmin M. Elnabawy, Rania A. Salama
article en
19 citations

Abstract

Developing robust and secure image encryption methods for transmitting multiple images in batches over unprotected networks has become imperative. This necessity arises from the limitations of single-image encryption techniques in managing the escalating volume of extensive data. This paper introduces a novel three-layer multiple-image encryption (MIE) technique to encrypt batch images based on three 2D-chaotic maps. All multiple-color images are divided into RGB channels in the first layer. The images in each channel go through a randomization process to be arranged at random before being combined to form a single image (batch) used as the input for the following layer. In the second layer, chaotic sequences for scrambling pixels in each channel independently are generated using Baker, Henon, and 2-D Logistic chaotic maps, resulting in a scrambled image. The diffusion process is applied in the final layer by independently changing the values of the pixels in each channel using different chaotic sequences generated from the three maps and the XORing operation. The efficiency of the proposed scheme is validated through key sensitivity, key space analysis, complexity analysis, entropy assessment, and tests, including horizontal, vertical, and diagonal correlation, MSE, PSNR, UACI, and NPCR. Moreover, experimental results and a thorough security analysis affirm that the proposed encryption technique has effectively attained confidentiality and robust resistance against various attacks.

Scientific ReportsVol. 14(1)
Suez University (EG), Zagazig University (EG)
Science and Technology Development Fund
Openalex Percentile: Top 4%
Chaos-based Image/Signal Encryption
4.73
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Multiple image encryption algorithm using channel randomization and multiple chaotic maps — Ahmed M. Elshewey, Khalid Mohamed Hosny, et al. · Scientific Reports (2024) | TGRS Research Map | TGRS