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Quantum image cryptography based on continuous chaotic maps

Quantum image cryptography based on continuous chaotic maps Images are significant data carriers because they are more challenging to transfer or store securely than text data because they include large amounts of digital data with high redundancy and volume. As a result, image security has grown in importance and relevance to researchers. Images can be shielded against a variety of risks with security, including eavesdropping and illegal copying and alteration. To transform an image into an unidentified format that can be sent via a medium, image encryption is utilized. Because of the potential quantum risk to the existing cryptographic encryption methods and the quick advancement towards the development of quantum computers, quantum image encryption algorithms have recently drawn increasing amounts of attention. The majority of quantum image encryption techniques such as diffusion and scrambling, involve two separate rounds. In this model, the three different chaotic maps are used separately for scrambling the images to determine the performance of the quantum image cryptography with different combinations of the model. At first, the hash256 algorithm is used for generating the quantum key and the forward diffusion takes place for diffusing the first pixel to the final pixel of the input image information. Then, the three different chaotic maps such as pixel permutation, Chen attractor and Lorenz attractor are used for scrambling the input image. Finally, the bit-level permutation and backward diffusion process are considered for the scrambled image. For evaluating the performance of the quantum image cryptography based on the three different chaotic maps, the NPCR, UACI, Entropy, SSIM, correlation characteristics and histogram analysis are determined. From this evaluation, the Lorenz attractor chaotic map performs better than the pixel permutation and Chen attractor. The attained NPCR, UACI, Entropy and SSIM of the CASIA2 dataset for Lorenz attractor are improved than the pixel permutation and Chen attractor. Thus, from the attained values, the Quantum Image Cryptography Based on a Continuous Chaotic Map such as the Lorenz attractor, performs better for the statistical and differential analysis than the other chaotic maps. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Microsystem Technologies Springer Journals

Quantum image cryptography based on continuous chaotic maps

Satre, Shilpa M.; Joshi, Bharti
Microsystem Technologies , Volume 31 (6) – Jun 1, 2025
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References (20)

Publisher
Springer Journals
Copyright
Copyright © The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature 2024
ISSN
0946-7076
eISSN
1432-1858
DOI
10.1007/s00542-024-05764-2
Publisher site
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Abstract

Images are significant data carriers because they are more challenging to transfer or store securely than text data because they include large amounts of digital data with high redundancy and volume. As a result, image security has grown in importance and relevance to researchers. Images can be shielded against a variety of risks with security, including eavesdropping and illegal copying and alteration. To transform an image into an unidentified format that can be sent via a medium, image encryption is utilized. Because of the potential quantum risk to the existing cryptographic encryption methods and the quick advancement towards the development of quantum computers, quantum image encryption algorithms have recently drawn increasing amounts of attention. The majority of quantum image encryption techniques such as diffusion and scrambling, involve two separate rounds. In this model, the three different chaotic maps are used separately for scrambling the images to determine the performance of the quantum image cryptography with different combinations of the model. At first, the hash256 algorithm is used for generating the quantum key and the forward diffusion takes place for diffusing the first pixel to the final pixel of the input image information. Then, the three different chaotic maps such as pixel permutation, Chen attractor and Lorenz attractor are used for scrambling the input image. Finally, the bit-level permutation and backward diffusion process are considered for the scrambled image. For evaluating the performance of the quantum image cryptography based on the three different chaotic maps, the NPCR, UACI, Entropy, SSIM, correlation characteristics and histogram analysis are determined. From this evaluation, the Lorenz attractor chaotic map performs better than the pixel permutation and Chen attractor. The attained NPCR, UACI, Entropy and SSIM of the CASIA2 dataset for Lorenz attractor are improved than the pixel permutation and Chen attractor. Thus, from the attained values, the Quantum Image Cryptography Based on a Continuous Chaotic Map such as the Lorenz attractor, performs better for the statistical and differential analysis than the other chaotic maps.

Journal

Microsystem Technologies – Springer Journals

Published: Jun 1, 2025

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