基于压缩感知的云辅助图像加密和数据隐藏双重保护系统

IF 0.6 Q4 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS International Journal of Digital Crime and Forensics Pub Date : 2021-11-01 DOI:10.4018/ijdcf.295812
Di Xiao, Jia Liang, Y. Xiang, Jiaqi Zhou
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引用次数: 0

摘要

在本文中,我们提出了一种基于压缩感知(CS)的方案,将加密和数据隐藏相结合,为云外包中的图像数据提供双重保护。为了提高效率和安全性,集成了不同的领域技术。数据持有者获得原始数据的样本后,将水印嵌入到样本中并进行加密,然后将保护后的样本发送到云端进行存储和恢复。在CS恢复过程中,Cloud无法获取原始数据或水印的任何信息。最后,用户可以提取水印,直接在稀疏域对云恢复的数据进行解密。同时,在水印提取后,用户的图像数据比未提取的数据更接近原始数据。此外,引入计数器(CTR)模式生成CS的测量矩阵,在避免测量矩阵存储的同时提高了安全性。实验结果表明,该方案能够高效地提供隐私保护和版权保护。
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Cloud-Assisted Image Double Protection System With Encryption and Data Hiding Based on Compressive Sensing
In this paper, we propose a compressive sensing(CS)-based scheme that combines encryption and data hiding to provide double protection to the image data in the cloud outsourcing. Different domain techniques are integrated for efficiency and security. After the data holder gets the sample of the raw data, he embeds watermark into sample and encrypts it, and then sends the protected sample to cloud for storage and recovery. Cloud cannot get any information about either the original data or watermark in the CS recovery process. Finally, users can extract the watermark and decrypt the data recovered by cloud directly in sparse domain. At the same time, after extracting the watermark, the image data of user will be closer to the original data compared with the data without extraction. Besides, the counter (CTR) mode is introduced to generate the measurement matrix of CS, which can improve security while avoiding the storage of measurement matrixes. The experimental results demonstrate that the scheme can provide both privacy protection and copyright protection with high efficiency.
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来源期刊
International Journal of Digital Crime and Forensics
International Journal of Digital Crime and Forensics COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS-
CiteScore
2.70
自引率
0.00%
发文量
15
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