Abstract
To ensure the reliability and integrity of data in the cloud storage server, some scholars provided various data integrity auditing schemes. However, the most existing data integrity auditing schemes only support the static data and may be unsuitable for the dynamic operations of data. To overcome this difficulty, we propose a fuzzy identity-based dynamic auditing of big data, which combines the structure of the Merkle hash tree (MHT) with the Index logic table (ILT). Our scheme not only performs the dynamic operations of data block in the ILT, namely modification, insertion and deletion, but also efficiently executes dynamic operations of the ILT on the structure of the MHT. We also elaborate the security, characteristics and performance analysis of the proposed scheme separately. The analysis results show that the proposed scheme costs less time than the structure of the original MHT to generate the root node hash value during the metadata generation phase and update the root node hash value during the dynamic operations. Furthermore, when users store the new ILT in local storage, they require lower communication cost to update root node hash value than users without storing the ILT, and fewer interactions between the cloud storage server and users in the dynamic operations process.
Highlights
The development of the big data era has brought tremendous pressure on storage capacity and cost [1]
Other techniques had been well studied, as exemplified by the physical layer security [2], [3], which utilized the specific attributes of communication links, it suffered from the unreliable performance because of the physical layer
In 2011, Wang et al [13] provided a scheme on the basis of the BLS, which combined the structure of Merkle hash tree (MHT) to support fully dynamic operations
Summary
The development of the big data era has brought tremendous pressure on storage capacity and cost [1]. C. Zhao et al.: Fuzzy Identity-Based Dynamic Auditing of Big Data on Cloud Storage. In Li et al [14] proposed a fuzzy identity-based data auditing scheme, but did not execute the dynamic operations. After the dynamic operations are completed, users update the new ILT and the according root node. B. CONTRIBUTIONS To overcome the exiting problems, we design a fuzzy identity-based dynamic auditing scheme of big data on cloud storage. If the users do not store the new ILT in local storage, dynamic operations for data blocks lead to the update of the root node. Users store the new ILT in our scheme and control the update of the root node by themselves. Analysis results show that the communication cost of users is lower than users who do not store ILT, and the interactions between the cloud storage server and users are fewer
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