The explosive generation of Internet of Things (IoT) data calls for cloud service providers (CSP) to further provide more secure and reliable transmission, storage, and management services. This requirement, however, goes against the honest and curious nature of CSP, to the extent that existing methods introduce the third-party audit (TPA) to check data security in the cloud. TPA solves the problem of unreliable CSP but puts a heavy burden on lightweight users because of the sheer amount of the pre-audit data processing work. In this paper, we establish an audit model based on a designed binary tree assisted by edge computing, which provides computing capability for the resource-constrained terminals. The data pre-processing task is offloaded to the edge, which reduces computing load and improves the efficiency of task processing. We propose an improved correlation mechanism between data blocks and nodes on the binary tree so that all nodes on the binary tree can be fully utilized while existing methods use only leaf nodes and thus are required to establish multiple binary trees. Moreover, to improve audit efficiency, the binary tree in the audit process is designed to be self-balanced. In experiments, we compare our methods with the traditional method and experimental results show that the proposed mechanism is more effective to store and manage big data, which is conducive to providing users with more secure IoT services.
Bibliographical noteFunding Information:
Above work was supported in part by Natural Science Foundation of Fujian Province of China (No. 2020J06023 and No. 2018J01092 ), the Major Project of Basic and Applied Research in Guangdong Universities under Grant 2017WZDXM012 , National Natural Science Foundation of China (NSFC) under Grant No. 61872154 and No. 61772148 and the Fujian Provincial Outstanding Youth Scientific Research Personnel Training Program .
- Audit model
- Binary tree
- Data security
- Edge computing
- Resource-constrained terminal