Efficient edge-based data integrity auditing in cloud storage

Abstract

Edge computing increasingly collaborates with cloud computing to support numerous applications that involve large data volumes and frequent data interactions. In cloud-edge collaboration environments, applications especially with high requirements for low data transmission delay often deploy frequently accessed client data replicas on edge servers to improve data access efficiency. Consequently, client data is often distributed across both cloud and edge servers in practice. Therefore, efficiently verifying the integrity of all client data poses a complex and urgent challenge. To address this issue, the paper introduces a novel data integrity auditing scheme capable of efficiently performing asynchronous integrity checks on client data across both edge and cloud servers. In our scheme, clients only generate partial block tags and upload them along with the data to the edge server. Edge server computes complete tags based on the partial tags, caches a small portion of frequently accessed data, and transfers the remaining data to the cloud server. For data verification, edge servers provide partial integrity proofs for cached data, supporting the cloud server to generate complete proofs for all challenged data. Thus, the auditors can verify all client data, regardless of its storage location. In our scheme, edge clients bear only about half of the computational workload of existing schemes. Additionally, the cloud server also offloads a portion of computational and storage tasks to edge servers, significantly improving the overall efficiency of data checking. We theoretically prove the security of our scheme, and experimental results demonstrate its efficiency and feasibility.