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    吕骁博 郭 耀 陈向群. 基于分割的数字图像云存储机制[J]. 计算机研究与发展, 2014, 51(5): 1129-1135.
    引用本文: 吕骁博 郭 耀 陈向群. 基于分割的数字图像云存储机制[J]. 计算机研究与发展, 2014, 51(5): 1129-1135.
    Lü Xiaobo, Guo Yao, and Chen Xiangqun. A Splitting-Based Cloud Storage Mechanism for Digital Images[J]. Journal of Computer Research and Development, 2014, 51(5): 1129-1135.
    Citation: Lü Xiaobo, Guo Yao, and Chen Xiangqun. A Splitting-Based Cloud Storage Mechanism for Digital Images[J]. Journal of Computer Research and Development, 2014, 51(5): 1129-1135.

    基于分割的数字图像云存储机制

    A Splitting-Based Cloud Storage Mechanism for Digital Images

    • 摘要: 随着云计算和数据中心的发展,数据处理和存储工作逐渐转移到云平台.通过云服务器存储数字图像可以解决图像存储和共享的问题,但是一些云服务器可能难以保证这些数字图像数据的可靠性和可用性,导致用户隐私泄露.提出一种基于分割的数字图像云存储机制,并采用了2种不同的图像分割算法:分块分割和分层分割.为了验证该机制,实现了一个支持隐私保护的数字图像云存储工具,针对不同图像分割方法进行了比较分析与实现,对所选的不同云服务器服务质量进行了测试.通过一系列实验,结论表明该机制可为数字图像云存储提供隐私保护、提高可靠性,并在一定程度上提高云存储的性能.

       

      Abstract: Due to the development of cloud computing and datacenters, the task of data processing and storage has migrated to the cloud platforms gradually. As a special kind of data, digital images contain a lot of private information, and require a huge amount of storage resources with frequent addition and deletion. Although storing digital images on cloud servers could solve some of these challenges, the quality of service provided by some of these servers is not reliable enough, especially when privacy issues are concerned. This paper proposes a splitting-based cloud storage mechanism for digital images. After splitting images into several blocks or layers and storing them into different cloud storage platforms, the privacy and reliability of these images can be enhanced. Two image splitting algorithms are proposed: block-based splitting and layer-based splitting. An image storage tool for privacy protection is implemented to demonstrate the mechanism. Experimental results show that the proposed techniques are able to provide privacy protection, at the same time enhancing the reliability and performance when storing digital images to the cloud. Performance under different cloud storage services, different splitting algorithms and different splitting granularities are also provided and analyzed. Finally, privacy-related issues and challenges are discussed.

       

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