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Noise-Resistant Image Encryption Scheme for Medical Images in the Chaos and Wavelet Domain
In this paper, a noise-resistant image encryption scheme is proposed. We have used a cubic-logistic map, Discrete Wavelet Transform (DWT), and bit-plane extraction method to encrypt the medical images at the bit-level rather than pixel-level. The proposed work is divided into three sections; In the...
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Published in: | IEEE access 2021, Vol.9, p.59108-59130 |
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description | In this paper, a noise-resistant image encryption scheme is proposed. We have used a cubic-logistic map, Discrete Wavelet Transform (DWT), and bit-plane extraction method to encrypt the medical images at the bit-level rather than pixel-level. The proposed work is divided into three sections; In the first and the last section, the image is encrypted in the spatial domain. While the middle section of the proposed algorithm is devoted to the frequency domain encryption in which DWT is incorporated. As the frequency domain encryption section is a sandwich between the two spatial domain encryption sections, we called it a "sandwich encryption." The proposed algorithm is lossless because it can decrypt the exact pixel values of an image. Along with this, we have also gauge the proposed scheme's performance using statistical analysis such as entropy, correlation, and contrast. The entropy values of the cipher images generated from the proposed encryption scheme are more remarkable than 7.99, while correlation values are very close to zero. Furthermore, the number of pixel change rate (NPCR) and unified average change intensity (UACI) for the proposed encryption scheme is higher than 99.4% and 33, respectively. We have also tested the proposed algorithm by performing attacks such as cropping and noise attacks on enciphered images, and we found that the proposed algorithm can decrypt the plaintext image with little loss of information, but the content of the original image is visible. |
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We have used a cubic-logistic map, Discrete Wavelet Transform (DWT), and bit-plane extraction method to encrypt the medical images at the bit-level rather than pixel-level. The proposed work is divided into three sections; In the first and the last section, the image is encrypted in the spatial domain. While the middle section of the proposed algorithm is devoted to the frequency domain encryption in which DWT is incorporated. As the frequency domain encryption section is a sandwich between the two spatial domain encryption sections, we called it a "sandwich encryption." The proposed algorithm is lossless because it can decrypt the exact pixel values of an image. Along with this, we have also gauge the proposed scheme's performance using statistical analysis such as entropy, correlation, and contrast. The entropy values of the cipher images generated from the proposed encryption scheme are more remarkable than 7.99, while correlation values are very close to zero. Furthermore, the number of pixel change rate (NPCR) and unified average change intensity (UACI) for the proposed encryption scheme is higher than 99.4% and 33, respectively. We have also tested the proposed algorithm by performing attacks such as cropping and noise attacks on enciphered images, and we found that the proposed algorithm can decrypt the plaintext image with little loss of information, but the content of the original image is visible.</description><identifier>ISSN: 2169-3536</identifier><identifier>EISSN: 2169-3536</identifier><identifier>DOI: 10.1109/ACCESS.2021.3071535</identifier><identifier>CODEN: IAECCG</identifier><language>eng</language><publisher>Piscataway: IEEE</publisher><subject>Algorithms ; bit-plane decomposition ; chaotic map ; Cryptography ; Discrete Wavelet Transform ; Discrete wavelet transform (DWT) ; Discrete wavelet transforms ; Elliptic curve cryptography ; Encryption ; Entropy ; Frequency domain analysis ; Image contrast ; medical images ; Medical imaging ; Noise ; Pixels ; Security ; security analysis of medical images ; Statistical analysis ; Transforms ; Wavelet transforms</subject><ispartof>IEEE access, 2021, Vol.9, p.59108-59130</ispartof><rights>Copyright The Institute of Electrical and Electronics Engineers, Inc. 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We have used a cubic-logistic map, Discrete Wavelet Transform (DWT), and bit-plane extraction method to encrypt the medical images at the bit-level rather than pixel-level. The proposed work is divided into three sections; In the first and the last section, the image is encrypted in the spatial domain. While the middle section of the proposed algorithm is devoted to the frequency domain encryption in which DWT is incorporated. As the frequency domain encryption section is a sandwich between the two spatial domain encryption sections, we called it a "sandwich encryption." The proposed algorithm is lossless because it can decrypt the exact pixel values of an image. Along with this, we have also gauge the proposed scheme's performance using statistical analysis such as entropy, correlation, and contrast. The entropy values of the cipher images generated from the proposed encryption scheme are more remarkable than 7.99, while correlation values are very close to zero. Furthermore, the number of pixel change rate (NPCR) and unified average change intensity (UACI) for the proposed encryption scheme is higher than 99.4% and 33, respectively. We have also tested the proposed algorithm by performing attacks such as cropping and noise attacks on enciphered images, and we found that the proposed algorithm can decrypt the plaintext image with little loss of information, but the content of the original image is visible.</description><subject>Algorithms</subject><subject>bit-plane decomposition</subject><subject>chaotic map</subject><subject>Cryptography</subject><subject>Discrete Wavelet Transform</subject><subject>Discrete wavelet transform (DWT)</subject><subject>Discrete wavelet transforms</subject><subject>Elliptic curve cryptography</subject><subject>Encryption</subject><subject>Entropy</subject><subject>Frequency domain analysis</subject><subject>Image contrast</subject><subject>medical images</subject><subject>Medical imaging</subject><subject>Noise</subject><subject>Pixels</subject><subject>Security</subject><subject>security analysis of medical images</subject><subject>Statistical analysis</subject><subject>Transforms</subject><subject>Wavelet transforms</subject><issn>2169-3536</issn><issn>2169-3536</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2021</creationdate><recordtype>article</recordtype><sourceid>ESBDL</sourceid><sourceid>DOA</sourceid><recordid>eNpNUV1L7DAQLaKgqL_Al4DPXZNOkjaPUlfvgh_gKoIvYTadull2mzWpF_z3dq2Iw8AMhznnDJwsOxN8IgQ3F5d1PZ3PJwUvxAR4KRSoveyoENrkoEDv_9kPs9OUVnyoaoBUeZS93gefKH-k5FOPXc9mG3wjNu1c_Nz2PnRs7pa0IdaGyO6o8Q7X401ivmP9kli9xJAYdg17wf-0pp5dhQ367iQ7aHGd6PRnHmfP19On-l9--3Azqy9vcyd51eclLAy0hlRjOKoFtM5olE6bwkgwVFDTglYN4NCVEgYWHCqQUHEDTmoNx9ls1G0Cruw2-g3GTxvQ228gxDeLsfduTVY3HLWSqLUhOcgspCi0axFVwx2JctA6H7W2Mbx_UOrtKnzEbnjfFkqUHKTiO0cYr1wMKUVqf10Ft7tM7JiJ3WVifzIZWGcjyxPRL8OAqXQp4QuUPoXK</recordid><startdate>2021</startdate><enddate>2021</enddate><creator>Shafique, Arslan</creator><creator>Ahmed, Jameel</creator><creator>Rehman, Mujeeb Ur</creator><creator>Hazzazi, Mohammad Mazyad</creator><general>IEEE</general><general>The Institute of Electrical and Electronics Engineers, Inc. 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subjects | Algorithms bit-plane decomposition chaotic map Cryptography Discrete Wavelet Transform Discrete wavelet transform (DWT) Discrete wavelet transforms Elliptic curve cryptography Encryption Entropy Frequency domain analysis Image contrast medical images Medical imaging Noise Pixels Security security analysis of medical images Statistical analysis Transforms Wavelet transforms |
title | Noise-Resistant Image Encryption Scheme for Medical Images in the Chaos and Wavelet Domain |
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