Efficient and Secure Storage Verification in Cloud-Assisted Industrial IoT Networks

Haiyang Yu, Hui Zhang, Zhen Yang, Yuwen Chen, Huan Liu

Abstract: The rapid development of Industrial IoT (IIoT) has caused the explosion of industrial data, which opens up promising possibilities for data analysis in IIoT networks. Due to the limitation of computation and storage capacity, IIoT devices choose to outsource the collected data to remote cloud servers. Unfortunately, the cloud storage service is not as reliable as it claims, whilst the loss of physical control over the cloud data makes it a significant challenge in ensuring the integrity of the data. Existing schemes are designed to check the data integrity in the cloud. However, it is still an open problem since IIoT devices have to devote lots of computation resources in existing schemes, which are especially not friendly to resource-constrained IIoT devices. In this paper, we propose an efficient storage verification approach for cloud-assisted industrial IoT platform by adopting a homomorphic hash function combined with polynomial commitment. The proposed approach can efficiently generate verification tags and verify the integrity of data in the industrial cloud platform for IIoT devices. Moreover, the proposed scheme can be extended to support privacy-enhanced verification and dynamic updates. We prove the security of the proposed approach under the random oracle model. Extensive experiments demonstrate the superior performance of our approach for resource-constrained devices in comparison with the state-of-the-art.