{"title":"遥感图像传输的新型安全方案:包含压缩和编码的综合方法","authors":"Haiyang Shen, Jinqing Li, Xiaoqiang Di, Xusheng Li, Zhenxun Liu, Makram Ibrahim","doi":"10.1007/s12145-024-01424-1","DOIUrl":null,"url":null,"abstract":"<p>With the advancement of technology and the maturity of various aerial imaging techniques, data proprietors have awareness of the importance of secure protection for remote sensing images. In order to protect sensitive data of images, we propose a secure encoding scheme for compressing remote sensing images to decrease potential risks of data disclosure associated with such images. First, we designed the Sin chaos paradigm for constructing chaotic systems in various dimensions. As a result through relevant experiments, this chaos paradigm demonstrated effective scalability and stability. In addition, DNA transposition methods have been introduced to extend DNA encoding, expanding the range of DNA encoding from 1 to 4 and achieving dynamic selection of DNA transposition methods. This method reduces potential threats that conflict with fixed DNA encoding methods. In addition, in order to ensure the security of symmetric encryption and the efficiency of asymmetric encryption during key transmission, an elliptical curve “ring” key hiding strategy is adopted. Although the key embedding occupies 1.2% of the space in the ciphertext image, data redundancy realizes the implicit transmission of the key, improving the decryption efficiency of remote sensing images. In response to the above research, we propose a secure compression encoding scheme based on Sin chaotic paradigm and DNA transposition to ensure the security of remote sensing images. After cropping the original remote sensing image to a size of 1/16, the original image can still be decrypted. In addition, when the noise attack reaches 0.3, the ciphertext image can also be restored. Performance analysis and experimental data results show that our proposed secure compression encoding scheme has excellent robustness and security.</p>","PeriodicalId":49318,"journal":{"name":"Earth Science Informatics","volume":"14 1","pages":""},"PeriodicalIF":2.7000,"publicationDate":"2024-08-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"A novel secure scheme for remote sensing image transmission: an integrated approach with compression and encoding\",\"authors\":\"Haiyang Shen, Jinqing Li, Xiaoqiang Di, Xusheng Li, Zhenxun Liu, Makram Ibrahim\",\"doi\":\"10.1007/s12145-024-01424-1\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p>With the advancement of technology and the maturity of various aerial imaging techniques, data proprietors have awareness of the importance of secure protection for remote sensing images. 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Although the key embedding occupies 1.2% of the space in the ciphertext image, data redundancy realizes the implicit transmission of the key, improving the decryption efficiency of remote sensing images. In response to the above research, we propose a secure compression encoding scheme based on Sin chaotic paradigm and DNA transposition to ensure the security of remote sensing images. After cropping the original remote sensing image to a size of 1/16, the original image can still be decrypted. In addition, when the noise attack reaches 0.3, the ciphertext image can also be restored. 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引用次数: 0
摘要
随着技术的进步和各种航空成像技术的成熟,数据所有者已经意识到安全保护遥感图像的重要性。为了保护图像的敏感数据,我们提出了一种用于压缩遥感图像的安全编码方案,以降低此类图像数据泄露的潜在风险。首先,我们设计了用于构建各种维度混沌系统的 Sin 混沌范式。通过相关实验,该混沌范式表现出了有效的可扩展性和稳定性。此外,我们还引入了DNA转置方法来扩展DNA编码,将DNA编码的范围从1扩展到4,并实现了DNA转置方法的动态选择。这种方法减少了与固定 DNA 编码方法相冲突的潜在威胁。此外,为了确保密钥传输过程中对称加密的安全性和非对称加密的效率,采用了椭圆曲线 "环形 "密钥隐藏策略。虽然密钥嵌入占据了密文图像 1.2% 的空间,但数据冗余实现了密钥的隐式传输,提高了遥感图像的解密效率。针对上述研究,我们提出了一种基于Sin混沌范式和DNA转置的安全压缩编码方案,以确保遥感图像的安全性。将原始遥感图像裁剪为 1/16 大小后,仍可解密原始图像。此外,当噪声攻击达到 0.3 时,密文图像也能还原。性能分析和实验数据结果表明,我们提出的安全压缩编码方案具有出色的鲁棒性和安全性。
A novel secure scheme for remote sensing image transmission: an integrated approach with compression and encoding
With the advancement of technology and the maturity of various aerial imaging techniques, data proprietors have awareness of the importance of secure protection for remote sensing images. In order to protect sensitive data of images, we propose a secure encoding scheme for compressing remote sensing images to decrease potential risks of data disclosure associated with such images. First, we designed the Sin chaos paradigm for constructing chaotic systems in various dimensions. As a result through relevant experiments, this chaos paradigm demonstrated effective scalability and stability. In addition, DNA transposition methods have been introduced to extend DNA encoding, expanding the range of DNA encoding from 1 to 4 and achieving dynamic selection of DNA transposition methods. This method reduces potential threats that conflict with fixed DNA encoding methods. In addition, in order to ensure the security of symmetric encryption and the efficiency of asymmetric encryption during key transmission, an elliptical curve “ring” key hiding strategy is adopted. Although the key embedding occupies 1.2% of the space in the ciphertext image, data redundancy realizes the implicit transmission of the key, improving the decryption efficiency of remote sensing images. In response to the above research, we propose a secure compression encoding scheme based on Sin chaotic paradigm and DNA transposition to ensure the security of remote sensing images. After cropping the original remote sensing image to a size of 1/16, the original image can still be decrypted. In addition, when the noise attack reaches 0.3, the ciphertext image can also be restored. Performance analysis and experimental data results show that our proposed secure compression encoding scheme has excellent robustness and security.
期刊介绍:
The Earth Science Informatics [ESIN] journal aims at rapid publication of high-quality, current, cutting-edge, and provocative scientific work in the area of Earth Science Informatics as it relates to Earth systems science and space science. This includes articles on the application of formal and computational methods, computational Earth science, spatial and temporal analyses, and all aspects of computer applications to the acquisition, storage, processing, interchange, and visualization of data and information about the materials, properties, processes, features, and phenomena that occur at all scales and locations in the Earth system’s five components (atmosphere, hydrosphere, geosphere, biosphere, cryosphere) and in space (see "About this journal" for more detail). The quarterly journal publishes research, methodology, and software articles, as well as editorials, comments, and book and software reviews. Review articles of relevant findings, topics, and methodologies are also considered.