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Assure deletion supporting dynamic insertion for outsourced data in cloud computing
International Journal of Distributed Sensor Networks ( IF 1.9 ) Pub Date : 2020-09-01 , DOI: 10.1177/1550147720958294
Changsong Yang 1, 2, 3 , Yueling Liu 1 , Xiaoling Tao 1, 2
Affiliation  

With the rapid development of cloud computing, an increasing number of data owners are willing to employ cloud storage service. In cloud storage, the resource-constraint data owners can outsource their large-scale data to the remote cloud server, by which they can greatly reduce local storage overhead and computation cost. Despite plenty of attractive advantages, cloud storage inevitably suffers from some new security challenges due to the separation of outsourced data ownership and its management, such as secure data insertion and deletion. The cloud server may maliciously reserve some data copies and return a wrong deletion result to cheat the data owner. Moreover, it is very difficult for the data owner to securely insert some new data blocks into the outsourced data set. To solve the above two problems, we adopt the primitive of Merkle sum hash tree to design a novel publicly verifiable cloud data deletion scheme, which can also simultaneously achieve provable data storage and dynamic data insertion. Moreover, an interesting property of our proposed scheme is that it can satisfy private and public verifiability without requiring any trusted third party. Furthermore, we formally prove that our proposed scheme not only can achieve the desired security properties, but also can realize the high efficiency and practicality.

中文翻译:

保证删除支持云计算中外包数据的动态插入

随着云计算的快速发展,越来越多的数据所有者愿意使用云存储服务。在云存储中,资源受限的数据所有者可以将自己的大规模数据外包给远程云服务器,从而大大降低本地存储开销和计算成本。尽管有很多诱人的优势,但由于外包数据所有权及其管理的分离,云存储不可避免地面临一些新的安全挑战,例如安全数据插入和删除。云服务器可能恶意保留部分数据副本并返回错误的删除结果以欺骗数据所有者。而且,数据所有者很难将一些新的数据块安全地插入到外包数据集中。为了解决以上两个问题,我们采用 Merkle sum 哈希树的原语设计了一种新颖的可公开验证的云数据删除方案,该方案还可以同时实现可证明的数据存储和动态数据插入。此外,我们提出的方案的一个有趣特性是它可以满足私人和公共可验证性,而无需任何受信任的第三方。此外,我们正式证明了我们提出的方案不仅可以实现所需的安全特性,而且可以实现高效率和实用性。
更新日期:2020-09-01
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