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arXiv 1712.04417cs.CR
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基于关键字的可委托存储证明

Keyword-Based Delegable Proofs of Storage

Binanda Sengupta, Sushmita Ruj

摘要:

终端存储容量有限的云用户(客户端)可以将批量数据外包给云存储服务器。客户可以在以后通过下载所需的数据文件来访问她的数据。然而,客户端外包给服务器的大部分数据文件通常本质上是归档的,客户端将其用于备份目的并且不太频繁地访问。因此,不受信任的服务器可以删除这些归档数据文件中的一些,以便节省一些空间(并将其分配给其他客户端)而不被客户端(数据所有者)检测到。存储证明使客户端能够审核其上传到服务器的数据文件,以确保这些文件的完整性。在这项工作中,我们介绍了一种类型的(选择性)存储证明,我们称之为基于关键字的可委托存储证明,其中客户端希望审计包含特定关键字的所有数据文件(例如,“重要”)。此外,它满足了公共可验证性的概念,其中客户端可以将审计任务委托给代表客户端审计与关键字对应的文件集的第三方审计员。我们正式定义了基于关键字的可委托存储证明协议的安全性。我们构造了这样一个协议的基础上现有的存储证明方案和分析我们的协议的安全性。我们认为,我们使用的技术可以应用于任何现有的公开可验证的存储证明方案的静态数据。最后,我们讨论了我们的建设效率。

英文摘要:

Cloud users (clients) with limited storage capacity at their end can outsource bulk data to the cloud storage server. A client can later access her data by downloading the required data files. However, a large fraction of the data files the client outsources to the server is often archival in nature that the client uses for backup purposes and accesses less frequently. An untrusted server can thus delete some of these archival data files in order to save some space (and allocate the same to other clients) without being detected by the client (data owner). Proofs of storage enable the client to audit her data files uploaded to the server in order to ensure the integrity of those files. In this work, we introduce one type of (selective) proofs of storage that we call keyword-based delegable proofs of storage, where the client wants to audit all her data files containing a specific keyword (e.g., "important"). Moreover, it satisfies the notion of public verifiability where the client can delegate the auditing task to a third-party auditor who audits the set of files corresponding to the keyword on behalf of the client. We formally define the security of a keyword-based delegable proof-of-storage protocol. We construct such a protocol based on an existing proof-of-storage scheme and analyze the security of our protocol. We argue that the techniques we use can be applied atop any existing publicly verifiable proof-of-storage scheme for static data. Finally, we discuss the efficiency of our construction.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

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