A Visually Secure Image Encryption Based on the Fractional Lorenz System and Compressive Sensing
Recently, generating visually secure cipher images by compressive sensing (CS) techniques has drawn much attention among researchers. However, most of these algorithms generate cipher images based on direct bit substitution and the underlying relationship between the hidden and modified data is not...
| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
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MDPI AG
2022-05-01
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| Series: | Fractal and Fractional |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2504-3110/6/6/302 |
| _version_ | 1797487308035850240 |
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| author | Hua Ren Shaozhang Niu Jiajun Chen Ming Li Zhen Yue |
| author_facet | Hua Ren Shaozhang Niu Jiajun Chen Ming Li Zhen Yue |
| author_sort | Hua Ren |
| collection | DOAJ |
| description | Recently, generating visually secure cipher images by compressive sensing (CS) techniques has drawn much attention among researchers. However, most of these algorithms generate cipher images based on direct bit substitution and the underlying relationship between the hidden and modified data is not considered, which reduces the visual security of cipher images. In addition, performing CS on plain images directly is inefficient, and CS decryption quality is not high enough. Thus, we design a novel cryptosystem by introducing vector quantization (VQ) into CS-based encryption based on a 3D fractional Lorenz chaotic system. In our work, CS compresses only the sparser error matrix generated from the plain and VQ images in the secret generation phase, which improves CS compression performance and the quality of decrypted images. In addition, a smooth function is used in the embedding phase to find the underlying relationship and determine relatively suitable modifiable values for the carrier image. All the secret streams are produced by updating the initial values and control parameters from the fractional chaotic system, and then utilized in CS, diffusion, and embedding. Simulation results demonstrate the effectiveness of the proposed method. |
| first_indexed | 2024-03-09T23:46:42Z |
| format | Article |
| id | doaj.art-5df2398762154bdba99c9437d5a01d42 |
| institution | Directory Open Access Journal |
| issn | 2504-3110 |
| language | English |
| last_indexed | 2024-03-09T23:46:42Z |
| publishDate | 2022-05-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Fractal and Fractional |
| spelling | doaj.art-5df2398762154bdba99c9437d5a01d422023-11-23T16:42:26ZengMDPI AGFractal and Fractional2504-31102022-05-016630210.3390/fractalfract6060302A Visually Secure Image Encryption Based on the Fractional Lorenz System and Compressive SensingHua Ren0Shaozhang Niu1Jiajun Chen2Ming Li3Zhen Yue4Beijing Key Lab of Intelligent Telecommunication Software and Multimedia, School of Computer, Beijing University of Posts and Telecommunications, Beijing 100876, ChinaBeijing Key Lab of Intelligent Telecommunication Software and Multimedia, School of Computer, Beijing University of Posts and Telecommunications, Beijing 100876, ChinaFukonnv Reseach, Guangzhou 510450, ChinaCollege of Computer and Information Engineering, Henan Normal University, Xinxiang 453007, ChinaFaculty of Education, Henan Normal University, Xinxiang 453007, ChinaRecently, generating visually secure cipher images by compressive sensing (CS) techniques has drawn much attention among researchers. However, most of these algorithms generate cipher images based on direct bit substitution and the underlying relationship between the hidden and modified data is not considered, which reduces the visual security of cipher images. In addition, performing CS on plain images directly is inefficient, and CS decryption quality is not high enough. Thus, we design a novel cryptosystem by introducing vector quantization (VQ) into CS-based encryption based on a 3D fractional Lorenz chaotic system. In our work, CS compresses only the sparser error matrix generated from the plain and VQ images in the secret generation phase, which improves CS compression performance and the quality of decrypted images. In addition, a smooth function is used in the embedding phase to find the underlying relationship and determine relatively suitable modifiable values for the carrier image. All the secret streams are produced by updating the initial values and control parameters from the fractional chaotic system, and then utilized in CS, diffusion, and embedding. Simulation results demonstrate the effectiveness of the proposed method.https://www.mdpi.com/2504-3110/6/6/302image encryptioncompressive sensingdiffusionfractional chaotic system |
| spellingShingle | Hua Ren Shaozhang Niu Jiajun Chen Ming Li Zhen Yue A Visually Secure Image Encryption Based on the Fractional Lorenz System and Compressive Sensing Fractal and Fractional image encryption compressive sensing diffusion fractional chaotic system |
| title | A Visually Secure Image Encryption Based on the Fractional Lorenz System and Compressive Sensing |
| title_full | A Visually Secure Image Encryption Based on the Fractional Lorenz System and Compressive Sensing |
| title_fullStr | A Visually Secure Image Encryption Based on the Fractional Lorenz System and Compressive Sensing |
| title_full_unstemmed | A Visually Secure Image Encryption Based on the Fractional Lorenz System and Compressive Sensing |
| title_short | A Visually Secure Image Encryption Based on the Fractional Lorenz System and Compressive Sensing |
| title_sort | visually secure image encryption based on the fractional lorenz system and compressive sensing |
| topic | image encryption compressive sensing diffusion fractional chaotic system |
| url | https://www.mdpi.com/2504-3110/6/6/302 |
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