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An improved data integrity validation model for cloud storage

机译:一种改进的云存储数据完整性验证模型

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Data integrity validation is considered to be an important tool to solve the problem that cloud subscribers cannot accurately know whether there are non-subjective changes in the data they upload to cloud servers. In this paper, a data integrity verification model based on dynamic successor tree index structure, Bloom filter and Merkle tree is proposed. The block labels generated according to the features of the dynamic successor tree index structure can sense whether changes have been made to the user's data, while the Merkle tree can track the cha~(*)nged data blocks, enabling the user to effectively verify the integrity of the data stored in the cloud server and provide more effective protection for data.
机译:数据完整性验证被认为是解决云订阅者无法准确了解其上传到云服务器的数据的非主观变化的重要工具。 本文提出了一种基于动态继承树索引结构,绽放过滤器和Merkle树的数据完整性验证模型。 根据动态后继树索引结构的特征生成的块标签可以感知是否已经对用户的数据进行了变化,而Merkle树可以跟踪CHA〜(*)NGEND数据块,使用户能够有效验证 存储在云服务器中的数据的完整性并为数据提供更有效的保护。

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