Efficient and secure image compression and encryption based on compressive sensing and four-dimensional hyperchaotic system

IF 6.8 1区 计算机科学 0 COMPUTER SCIENCE, INFORMATION SYSTEMS
Ming Yao , Hongwei Deng , Zhong Chen , Pan Zhang
{"title":"Efficient and secure image compression and encryption based on compressive sensing and four-dimensional hyperchaotic system","authors":"Ming Yao ,&nbsp;Hongwei Deng ,&nbsp;Zhong Chen ,&nbsp;Pan Zhang","doi":"10.1016/j.ins.2025.122430","DOIUrl":null,"url":null,"abstract":"<div><div>With the growing awareness of privacy protection, the security of image data during network transmission has become a focal point of concern. Reducing computational complexity and improving transmission efficiency while meeting high-security requirements has become a primary focus of current research. To address this, we propose a novel image privacy protection scheme that combines compressive sensing with chaotic encryption, aiming to ensure image privacy and security while enhancing transmission and storage efficiency. We employ compressive sensing technology to achieve efficient compression of image data. Unlike traditional compression and encryption schemes, the proposed method does not require explicit sparsification preprocessing, thereby avoiding the complex operations introduced by signal transformations and simplifying the signal recovery process. To enhance encryption security, a four-dimensional hyperchaotic system with stronger chaotic properties is designed to generate highly random and unpredictable key streams, ensuring the security of the encrypted data. Furthermore, this paper combines disjoint Latin squares with fractal generation strategies to design a new fractal index matrix, based on which a novel image permutation scheme is proposed. This scheme effectively eliminates the linear relationships and correlations between adjacent pixels, achieving global pixel permutation. Coupled with the proposed dual-channel bidirectional diffusion structure, the algorithm effectively diffuses pixel information across the entire image, increasing the complexity and unpredictability of the image encryption process. Experimental results indicate that the proposed algorithm exhibits excellent performance in terms of compression efficiency, encryption effectiveness, and resistance to attacks, providing a highly efficient and reliable solution in the field of image compression and encryption.</div></div>","PeriodicalId":51063,"journal":{"name":"Information Sciences","volume":"719 ","pages":"Article 122430"},"PeriodicalIF":6.8000,"publicationDate":"2025-06-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Information Sciences","FirstCategoryId":"94","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0020025525005626","RegionNum":1,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"0","JCRName":"COMPUTER SCIENCE, INFORMATION SYSTEMS","Score":null,"Total":0}
引用次数: 0

Abstract

With the growing awareness of privacy protection, the security of image data during network transmission has become a focal point of concern. Reducing computational complexity and improving transmission efficiency while meeting high-security requirements has become a primary focus of current research. To address this, we propose a novel image privacy protection scheme that combines compressive sensing with chaotic encryption, aiming to ensure image privacy and security while enhancing transmission and storage efficiency. We employ compressive sensing technology to achieve efficient compression of image data. Unlike traditional compression and encryption schemes, the proposed method does not require explicit sparsification preprocessing, thereby avoiding the complex operations introduced by signal transformations and simplifying the signal recovery process. To enhance encryption security, a four-dimensional hyperchaotic system with stronger chaotic properties is designed to generate highly random and unpredictable key streams, ensuring the security of the encrypted data. Furthermore, this paper combines disjoint Latin squares with fractal generation strategies to design a new fractal index matrix, based on which a novel image permutation scheme is proposed. This scheme effectively eliminates the linear relationships and correlations between adjacent pixels, achieving global pixel permutation. Coupled with the proposed dual-channel bidirectional diffusion structure, the algorithm effectively diffuses pixel information across the entire image, increasing the complexity and unpredictability of the image encryption process. Experimental results indicate that the proposed algorithm exhibits excellent performance in terms of compression efficiency, encryption effectiveness, and resistance to attacks, providing a highly efficient and reliable solution in the field of image compression and encryption.
基于压缩感知和四维超混沌系统的高效安全图像压缩与加密
随着人们隐私保护意识的增强,图像数据在网络传输过程中的安全性成为人们关注的焦点。在满足高安全性要求的同时,降低计算复杂度,提高传输效率已成为当前研究的重点。为了解决这一问题,我们提出了一种将压缩感知与混沌加密相结合的图像隐私保护方案,在保证图像隐私和安全的同时提高传输和存储效率。采用压缩感知技术对图像数据进行高效压缩。与传统的压缩和加密方案不同,该方法不需要明确的稀疏化预处理,从而避免了信号变换带来的复杂操作,简化了信号恢复过程。为了提高加密安全性,设计了一个具有更强混沌特性的四维超混沌系统,生成高度随机和不可预测的密钥流,保证加密数据的安全性。在此基础上,结合分形生成策略设计了新的分形指标矩阵,并在此基础上提出了一种新的图像排列方案。该方案有效地消除了相邻像素之间的线性关系和相关性,实现了像素的全局排列。结合所提出的双通道双向扩散结构,该算法有效地将像素信息扩散到整个图像,增加了图像加密过程的复杂性和不可预测性。实验结果表明,该算法在压缩效率、加密有效性和抗攻击性能方面均表现出优异的性能,为图像压缩和加密领域提供了高效可靠的解决方案。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 求助全文
来源期刊
Information Sciences
Information Sciences 工程技术-计算机:信息系统
CiteScore
14.00
自引率
17.30%
发文量
1322
审稿时长
10.4 months
期刊介绍: Informatics and Computer Science Intelligent Systems Applications is an esteemed international journal that focuses on publishing original and creative research findings in the field of information sciences. We also feature a limited number of timely tutorial and surveying contributions. Our journal aims to cater to a diverse audience, including researchers, developers, managers, strategic planners, graduate students, and anyone interested in staying up-to-date with cutting-edge research in information science, knowledge engineering, and intelligent systems. While readers are expected to share a common interest in information science, they come from varying backgrounds such as engineering, mathematics, statistics, physics, computer science, cell biology, molecular biology, management science, cognitive science, neurobiology, behavioral sciences, and biochemistry.
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:604180095
Book学术官方微信