Cloud storage data integrity audit method based on b-tree Bloom filter

Abstract

The invention discloses a cloud storage data integrity auditing method based on a B-Tree Bloom filter. The method comprises the following sequentially-conducted steps of 1 data pre-processing, 2 datablock signature generating, 3 data storing, 4 integrity challenging, 5 challenge responding and 6 verification result calculating. When the method is used for cloud storage data integrity auditing, little storage of a server is occupied, the calculation efficiency is high, the operation speed and the reaction speed of the server are guaranteed, dynamic operations on data are supported, the data integrity auditing efficiency can be improved, and public auditing can be achieved.

Description

technical field [0001] The invention belongs to the technical field of big data and cloud computing security, in particular to a B-Tree Bloom filter-based cloud storage data integrity audit method. Background technique [0002] With the rapid development of big data technology, cloud storage, which is the basis of big data, also develops accordingly. However, with the rapid development of cloud storage, its data security is facing great challenges. Among the top 12 cloud security threats released by the Cloud Security Alliance, data leakage, malicious insider attacks and permanent data loss pose a huge threat to cloud storage data integrity. The data stored by users in the cloud may be peeped, modified and damaged by other users or cloud service providers. Some cloud service providers hide data loss from users out of self-reputation protection. Therefore, an efficient data integrity system is urgently needed. sex audit method. [0003] Common data integrity auditing metho...

AI Technical Summary

Problems solved by technology

Li et al. proposed an integrity audit method based on bilinear groups. This method constructs a bilinear map based on the Hellman computational difficulty problem for verifying metadata calculations, which reduces the cost of client-side implementation of the audit protocol initialization phase. However, due to The structure used by the audit process is complex, thus reducing verification efficiency

Hussien et al. proposed a data integrity audit method that does not use a homomorphic encryption algorithm. This method uses double-block transmission and encrypted hash functions to check the integrity of data stored in the cloud, which reduces the amount of client-side calculations, but increases auxiliary Storage space increases the risk of privacy leakage

Zhang et al. proposed a new public audit method, which uses the rb2-3 tree as a verification tool to achieve public verification and dynamic data auditing, but this method still has the problems of complex calculation and long verification path

Li Yong et al. used a multi-branch tree to determine the correctness of the location of the data block. This method reduces the computational burden of each entity in the audit model and simplifies the dynamic update process, but requires more auxiliary information when cloud computing holds evidence. Increased communication overhead between the cloud and the audit side

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