Supporting Efficient Dynamic Update in Public Integrity Verification of Cloud Data

Jiawei Wan, Shijie Jia, Limin Liu, Yang Zhang

Abstract: Cloud storage is an increasingly popular service of cloud computing, which can provide convenient on-demand data outsourcing services and release the burden of maintaining local data for both individuals and organizations. However, the cloud service providers are not fully trusted by the users. The reason is that the users lose physical control of their cloud data, and the cloud service providers may conceal the status of the data when encountering data loss accidents for reputation. Therefore, it is critical for users to efficiently verify the integrity of cloud data.In this paper, we propose a public integrity verification scheme to support efficient dynamic update of cloud data based on Merkle Hash Tree linked list (MHT-list), which is a novel two-dimensional data structure we designed. This structure utilizes multiple merkle hash trees (MHTs) and a linked list to record data information at the cloud service provider side. Meanwhile, we exploit the structural advantages of the MHT-list to make our scheme more efficient in dynamic update and integrity verification than existing works. Moreover, we formally prove the security of the proposed scheme and evaluate the performance of our scheme by concrete extensive experiments. The results demonstrate that our proposed scheme achieves dynamic update effectively in public integrity verification of cloud data, and outperforms the previous works in computation and communication overhead.