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Privacy preserving file auditing schemes for cloud storage using verifiable random function

机译:使用可验证随机函数保留云存储的隐私保留文件审核方案

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摘要

Users leverage the cloud storage to store data by uploading files to the cloud storage. They can use it to share files to work on collaborative projects. However, during administrative operations by cloud storage service provider (CSSP), there may be some inadvertent corruption of files during data migration and backup. Due to heavy demands, the cloud service provider may not update the desired files immediately when requested by the owner. As a result, a user of the file may receive an obsolete file. To ensure integrity and freshness of files, third party auditing (TPA) services should be supported by CSSP while maintaining the confidentiality of user files and preserving privacy of users. In this paper, three privacy preserving auditing schemes for files stored in cloud has been proposed. Verifiable random function, merkle hash tree and ciphertext-policy attribute-based encryption has been used to achieve the desired goals.
机译:用户利用云存储通过将文件上传到云存储来存储数据。他们可以使用它来共享文件来处理协作项目。但是,在云存储服务提供商(CSSP)的行政操作期间,在数据迁移和备份期间可能存在一些无意中的文件损坏。由于需求量沉重,云服务提供商可能不会在所有者请求时立即更新所需的文件。结果,文件的用户可以接收过时的文件。为了确保文件的完整性和新鲜度,CSSP应支持第三方审核(TPA)服务,同时保持用户文件的机密性并保留用户的隐私。在本文中,提出了三个隐私保留了存储在云中的文件的审计方案。可验证随机函数,Merkle哈希树和基于密文策略的加密已用于实现所需的目标。

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