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A secure cloud storage system supporting privacy-preserving fuzzy deduplication

机译:安全的云存储系统,支持隐私保护的模糊重复数据删除

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摘要

Deduplication is an important technology in the cloud storage service. For protecting user privacy, sensitive data usually have to be encrypted before outsourcing. This makes secure data deduplication a challenging task. Although convergent encryption is used to securely eliminate duplicate copies on the encrypted data, these secure deduplication techniques support only exact data deduplication. That is, there is no tolerance of differences in traditional deduplication schemes. This requirement is too strict for multimedia data including image. For images, typical modifications such as resizing and compression only change their binary presentation but maintain human visual perceptions, which should be eliminated as duplicate copies. Those perceptual similar images occupy a lot of storage space on the remote server and greatly affect the efficiency of deduplication system. In this paper, we first formalize and solve the problem of effective fuzzy image deduplication while maintaining user privacy. Our solution eliminates duplicated images based on the measurement of image similarity over encrypted data. The robustness evaluation is given and demonstrates that this fuzzy deduplication system is able to duplicate perceptual similar images, which optimizes the storage and bandwidth overhead greatly in cloud storage service.
机译:重复数据删除是云存储服务中的一项重要技术。为了保护用户隐私,通常必须在外包之前对敏感数据进行加密。这使得安全的重复数据删除成为一项艰巨的任务。尽管使用收敛加密来安全地消除加密数据上的重复副本,但是这些安全重复数据删除技术仅支持精确的重复数据删除。也就是说,传统的重复数据删除方案没有容忍差异的能力。对于包括图像的多媒体数据,此要求太严格。对于图像,典型的修改(例如调整大小和压缩)仅会更改其二进制表示形式,但会保留人类的视觉感知,因此应将其作为重复副本删除。这些感知相似的映像会占用远程服务器上的大量存储空间,并极大地影响重复数据删除系统的效率。在本文中,我们首先形式化并解决了有效的模糊图像重复数据删除问题,同时又保持了用户隐私。我们的解决方案基于对加密数据的图像相似性度量来消除重复的图像。给出了鲁棒性评估,并证明了该模糊重复数据删除系统能够复制感知相似的图像,从而极大地优化了云存储服务中的存储和带宽开销。

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