Image encryption algorithm for crowd data based on a new hyperchaotic system and Bernstein polynomial
Abstract A new two‐dimensional chaotic system in the form of a cascade structure is designed, which is derived from the Chebyshev system and the infinite collapse system. Performance analysis including trajectory, Lyapunov exponent and approximate entropy indicate that it has a larger chaotic range,...
Main Authors: | , , , |
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Format: | Article |
Language: | English |
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Wiley
2021-12-01
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Series: | IET Image Processing |
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Online Access: | https://doi.org/10.1049/ipr2.12237 |
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author | Donghua Jiang Lidong Liu Xingyuan Wang Xianwei Rong |
author_facet | Donghua Jiang Lidong Liu Xingyuan Wang Xianwei Rong |
author_sort | Donghua Jiang |
collection | DOAJ |
description | Abstract A new two‐dimensional chaotic system in the form of a cascade structure is designed, which is derived from the Chebyshev system and the infinite collapse system. Performance analysis including trajectory, Lyapunov exponent and approximate entropy indicate that it has a larger chaotic range, better ergodicity and more complex chaotic behaviour than those of advanced two‐dimensional chaotic system recently proposed. Moreover, to protect the security of the crowd image data, the newly designed two‐dimensional chaotic system is utilized to propose a visually meaningful image cryptosystem combined with singular value decomposition and Bernstein polynomial. First, the plain image is compressed by singular value decomposition, and then encrypted to the noise‐like cipher image by scrambling and diffusion algorithm. Later, the steganographic image is obtained by randomly embedding the cipher image into a carrier image in spatial domain through the Bernstein polynomial‐based embedding method, thereby realizing the double security of image information and image appearance. Besides, the visual quality of the steganographic image can be improved by the adjustment factor according to different carrier images during the embedding process. Ultimately, security analyses indicate that it has higher encryption efficiency (2 Mbps) and the visual quality of steganography image can reach 39 dB. |
first_indexed | 2024-04-11T07:28:13Z |
format | Article |
id | doaj.art-02e692f490444a0f990cac1f9fd156ca |
institution | Directory Open Access Journal |
issn | 1751-9659 1751-9667 |
language | English |
last_indexed | 2024-04-11T07:28:13Z |
publishDate | 2021-12-01 |
publisher | Wiley |
record_format | Article |
series | IET Image Processing |
spelling | doaj.art-02e692f490444a0f990cac1f9fd156ca2022-12-22T04:36:59ZengWileyIET Image Processing1751-96591751-96672021-12-0115143698371710.1049/ipr2.12237Image encryption algorithm for crowd data based on a new hyperchaotic system and Bernstein polynomialDonghua Jiang0Lidong Liu1Xingyuan Wang2Xianwei Rong3School of Information Engineering Chang'an University Xian ChinaSchool of Information Engineering Chang'an University Xian ChinaSchool of Information Science and Technology Dalian Maritime University Dalian ChinaPhysics and Electronic Engineering School Harbin Normal University Harbin ChinaAbstract A new two‐dimensional chaotic system in the form of a cascade structure is designed, which is derived from the Chebyshev system and the infinite collapse system. Performance analysis including trajectory, Lyapunov exponent and approximate entropy indicate that it has a larger chaotic range, better ergodicity and more complex chaotic behaviour than those of advanced two‐dimensional chaotic system recently proposed. Moreover, to protect the security of the crowd image data, the newly designed two‐dimensional chaotic system is utilized to propose a visually meaningful image cryptosystem combined with singular value decomposition and Bernstein polynomial. First, the plain image is compressed by singular value decomposition, and then encrypted to the noise‐like cipher image by scrambling and diffusion algorithm. Later, the steganographic image is obtained by randomly embedding the cipher image into a carrier image in spatial domain through the Bernstein polynomial‐based embedding method, thereby realizing the double security of image information and image appearance. Besides, the visual quality of the steganographic image can be improved by the adjustment factor according to different carrier images during the embedding process. Ultimately, security analyses indicate that it has higher encryption efficiency (2 Mbps) and the visual quality of steganography image can reach 39 dB.https://doi.org/10.1049/ipr2.12237Interpolation and function approximation (numerical analysis)Linear algebra (numerical analysis)CryptographyOptical, image and video signal processingInterpolation and function approximation (numerical analysis)Linear algebra (numerical analysis) |
spellingShingle | Donghua Jiang Lidong Liu Xingyuan Wang Xianwei Rong Image encryption algorithm for crowd data based on a new hyperchaotic system and Bernstein polynomial IET Image Processing Interpolation and function approximation (numerical analysis) Linear algebra (numerical analysis) Cryptography Optical, image and video signal processing Interpolation and function approximation (numerical analysis) Linear algebra (numerical analysis) |
title | Image encryption algorithm for crowd data based on a new hyperchaotic system and Bernstein polynomial |
title_full | Image encryption algorithm for crowd data based on a new hyperchaotic system and Bernstein polynomial |
title_fullStr | Image encryption algorithm for crowd data based on a new hyperchaotic system and Bernstein polynomial |
title_full_unstemmed | Image encryption algorithm for crowd data based on a new hyperchaotic system and Bernstein polynomial |
title_short | Image encryption algorithm for crowd data based on a new hyperchaotic system and Bernstein polynomial |
title_sort | image encryption algorithm for crowd data based on a new hyperchaotic system and bernstein polynomial |
topic | Interpolation and function approximation (numerical analysis) Linear algebra (numerical analysis) Cryptography Optical, image and video signal processing Interpolation and function approximation (numerical analysis) Linear algebra (numerical analysis) |
url | https://doi.org/10.1049/ipr2.12237 |
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