A Novel Lossless Medical Image Encryption Scheme Based on Game Theory With Optimized ROI Parameters and Hidden ROI Position
Medical images contain a large amount of patients' private information. The theft and destruction of medical images will cause irreparable losses to patients and medical institutions. In order to detect the region of interest(ROI) accurately, avoid leakage of ROI position information, and reali...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
| Published: |
IEEE
2020-01-01
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| Series: | IEEE Access |
| Subjects: | |
| Online Access: | https://ieeexplore.ieee.org/document/9133584/ |
| _version_ | 1818857013167259648 |
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| author | Jian Zhou Jinqing Li Xiaoqiang Di |
| author_facet | Jian Zhou Jinqing Li Xiaoqiang Di |
| author_sort | Jian Zhou |
| collection | DOAJ |
| description | Medical images contain a large amount of patients' private information. The theft and destruction of medical images will cause irreparable losses to patients and medical institutions. In order to detect the region of interest(ROI) accurately, avoid leakage of ROI position information, and realize lossless recovery of transform domain encryption, we propose a novel lossless medical image encryption scheme based on game theory with optimized ROI parameters and hidden ROI position. In the encryption process, the ROI is a pixel-level transformed to achieve the lossless decryption of medical images and protect medical image information from loss. At the same time, the position information of the ROI is effectively hidden, and leakage of the position information during transmission is avoided. In addition, the quantum cell neural network(QCNN) hyperchaotic system generates random sequence to scramble and diffuse the ROI. Most important of all, the quantitative analysis method of ROI parameters is given, and the optimal balance between encryption speed and encryption security performance is achieved by using game theory. Simulation experiments and numerical analysis verify that the scheme achieves optimized and lossless encryption and decryption of images, and can flexibly and reliably protect the medical images of different types and structures against various attacks. |
| first_indexed | 2024-12-19T08:33:38Z |
| format | Article |
| id | doaj.art-46e8193b321740afb31753cf6fb9f884 |
| institution | Directory Open Access Journal |
| issn | 2169-3536 |
| language | English |
| last_indexed | 2024-12-19T08:33:38Z |
| publishDate | 2020-01-01 |
| publisher | IEEE |
| record_format | Article |
| series | IEEE Access |
| spelling | doaj.art-46e8193b321740afb31753cf6fb9f8842022-12-21T20:29:07ZengIEEEIEEE Access2169-35362020-01-01812221012222810.1109/ACCESS.2020.30075509133584A Novel Lossless Medical Image Encryption Scheme Based on Game Theory With Optimized ROI Parameters and Hidden ROI PositionJian Zhou0https://orcid.org/0000-0002-2987-6626Jinqing Li1https://orcid.org/0000-0002-5580-2794Xiaoqiang Di2https://orcid.org/0000-0001-9432-4564School of Computer Science and Technology, Changchun University of Science and Technology, Changchun, ChinaSchool of Computer Science and Technology, Changchun University of Science and Technology, Changchun, ChinaSchool of Computer Science and Technology, Changchun University of Science and Technology, Changchun, ChinaMedical images contain a large amount of patients' private information. The theft and destruction of medical images will cause irreparable losses to patients and medical institutions. In order to detect the region of interest(ROI) accurately, avoid leakage of ROI position information, and realize lossless recovery of transform domain encryption, we propose a novel lossless medical image encryption scheme based on game theory with optimized ROI parameters and hidden ROI position. In the encryption process, the ROI is a pixel-level transformed to achieve the lossless decryption of medical images and protect medical image information from loss. At the same time, the position information of the ROI is effectively hidden, and leakage of the position information during transmission is avoided. In addition, the quantum cell neural network(QCNN) hyperchaotic system generates random sequence to scramble and diffuse the ROI. Most important of all, the quantitative analysis method of ROI parameters is given, and the optimal balance between encryption speed and encryption security performance is achieved by using game theory. Simulation experiments and numerical analysis verify that the scheme achieves optimized and lossless encryption and decryption of images, and can flexibly and reliably protect the medical images of different types and structures against various attacks.https://ieeexplore.ieee.org/document/9133584/Game theorylossless decryptionmedical image encryptionquantum cell neural networkregion of interestselective image encryption |
| spellingShingle | Jian Zhou Jinqing Li Xiaoqiang Di A Novel Lossless Medical Image Encryption Scheme Based on Game Theory With Optimized ROI Parameters and Hidden ROI Position IEEE Access Game theory lossless decryption medical image encryption quantum cell neural network region of interest selective image encryption |
| title | A Novel Lossless Medical Image Encryption Scheme Based on Game Theory With Optimized ROI Parameters and Hidden ROI Position |
| title_full | A Novel Lossless Medical Image Encryption Scheme Based on Game Theory With Optimized ROI Parameters and Hidden ROI Position |
| title_fullStr | A Novel Lossless Medical Image Encryption Scheme Based on Game Theory With Optimized ROI Parameters and Hidden ROI Position |
| title_full_unstemmed | A Novel Lossless Medical Image Encryption Scheme Based on Game Theory With Optimized ROI Parameters and Hidden ROI Position |
| title_short | A Novel Lossless Medical Image Encryption Scheme Based on Game Theory With Optimized ROI Parameters and Hidden ROI Position |
| title_sort | novel lossless medical image encryption scheme based on game theory with optimized roi parameters and hidden roi position |
| topic | Game theory lossless decryption medical image encryption quantum cell neural network region of interest selective image encryption |
| url | https://ieeexplore.ieee.org/document/9133584/ |
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