Merkle multi-branch hash tree-based dynamic data integrity auditing for B5G network cloud storage

Abstract

In the Beyond 5th Generation (B5G) mobile communication network, data transmission speed will be higher, and communication time latency will be minimized, it also brings new security challenges to data management and privacy protection. Aiming at the problems faced by the data integrity audit for B5G network cloud storage, such as complex dynamic data updating, a large number of users, we propose a Merkle Multi-branch Hash Tree (MMHT)-based data integrity auditing scheme for B5G network cloud storage. The scheme involves five entities and eight phases. We propose a multi-branch double-linked Merkle Hash Tree structure to store and audit dynamic data. We conduct correctness analysis and security analysis to this scheme. The results show that our scheme can meet the requirements of data integrity audit and counter six types of data integrity attack. We conduct theoretical comparative analysis. Compared with other schemes, the computational overhead of data owner (DO) is reduced by m times (m represents the number of data blocks). Relevant experiments are conducted with a 5G real-world dataset, and the experiments show that on the order of million data, the construction time of MHT is about 2.48 times that of MMHT in terms of Merkle tree. The verification time of MHT is about 12.83 times that of MMHT. When the data scale reaches millions, the time to generate user keys in the 4G environment is 6.49 times that of in the B5G environment. When the number of bilinear pairings reaches one million, the verification time of Third-Party Auditors (TPA) for 10,000 encrypted data entries is only 1.07 times that of 1,000 entries, indicating that our scheme can be scaled for use with large datasets. Compared with other schemes, our solution improves the efficiency and security of dynamic data integrity auditing in the B5G network environment.