Computer Engineering and Applications ›› 2018, Vol. 54 ›› Issue (4): 90-97.DOI: 10.3778/j.issn.1002-8331.1707-0304

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Batch remote data integrity checking protocol with corrupted data location

WANG Tianqi, PANG Xiaoqiong, REN Mengqi   

  1. School of Data Science and Technology, North University of China, Taiyuan 030051, China
  • Online:2018-02-15 Published:2018-03-07



  1. 中北大学 大数据学院,太原 030051

Abstract: The Remote Data Integrity Checking(RDIC), which can enable the users to verify the integrity of the outsourced data through a small amount of interaction with the server, is an important technology to ensure the security of cloud data. In reality, the cloud storage service is generally between multiple users and multiple servers. Recently, many RDIC schemes that support batch verification for multi-user and multi-server storage have been proposed. But after the batch verification fails, these schemes can’t determine the error data owners or the servers where the corrupted data is stored at one challenge process. It proposes a batch scheme with corrupted data positioning by utilizing Merkle Hash Tree(MHT), which can locate the damaged data owners and storage server where they store while the batch verification fails.

Key words: Remote Data Integrity Checking(RDIC), corrupted data location, batch verification, cloud storage security, Merkle Hash Tree(MHT)

摘要: 远程数据完整性验证技术是保证云数据安全的一种重要技术,能通过与服务器进行少量交互,验证外包数据是否完整。在现实中,云存储服务通常是在多用户与多服务器之间存在的,最近多用户与多服务器环境下的批处理验证方案陆续被提出。但这些方案在数据出错后,往往于一次挑战中无法判定错误数据的拥有者或所在服务器。利用Merkle Hash Tree(MHT)提出了一种支持错误数据定位的批处理校验方案,可以在批处理校验不通过后,同时定位出错误数据的拥有者与其所存储的服务器。

关键词: 远程数据完整性验证(RDIC), 错误数据定位, 批处理验证, 云存储安全, Merkle Hash Tree(MHT)