云存储环境下基于模格算法的数据存储完整度检测

Data Storage Integrity Detection Based on Modular Lattice Algorithm in Cloud Storage Environment

在云存储环境下进行数据保存后,需要依托于数据持有性证明检测数据存储完整度,每次验证的计算较为庞大,导致完整度检测的时间较长.对此,提出存储环境下基于模格算法的数据存储完整度检测方法 .基于热点循迹的数据分块技术,得到待检测的存储数据子块.根据数据块数量搭建包含众多叶子节点的多分支路径树,并通过哈希值匹配实现验证数据块动态更新.考虑数据存储完整度检测的3种参与实体,建立包含6种算法的验证机制,指导完整度检测的具体流程.最后,利用模格算法实现数据存储完整度检测.实验结果表明:在数据量为1 024 MB时,采用所提方法进行数据存储完整度检测的时间开销仅为3.5 s,满足了云存储数据检测要求.

After data are saved in a cloud storage environment,it is necessary to rely on proof of data ownership to detect the integrity of data storage.The calculation for each verification is relatively large,resulting in a longer time for integrity detection.To address this,a data storage integrity detection method based on modular lattice algorithm in a storage environment is proposed.Based on the hot spot tracking data partitioning technology,the storage data sub blocks are to be detected.A multi-branch path tree containing numerous leaf nodes based on data blocksis built,and the dynamic update of data blocks is verified through hash value matching.The study considers three participating entities for data storage integrity detection,establishes a verification mechanism that includes six algorithms,and guides the specific process of integrity detection.Finally,the modular lattice algorithm is used to achieve data storage integrity detection.The experimental results show that when the data volume is 1024 MB,the time cost of using the proposed method for data storage integrity detection is only 3.5 s,which meets the requirements of cloud storage data detection.