Collusion-Resistant Multi-Replica Data Auditing with Optimized Metadata Generation

To ensure data robustness, users typically create replicas of critical data and store them on multiple servers. However, due to server failures or malicious attacks, these replicas may face the risk of loss or tampering. Therefore, periodic auditing of data replicas is necessary to ensure their integrity. Existing solutions perform periodic auditing with generating metadata for each replica individually. However, generating auditing metadata for every replica incurs significant computational overhead, and storing metadata for multiple replicas also imposes a considerable storage burden. To reduce this overhead and optimize the efficiency of auditing towards multiple replicas, we propose collusion-resistant multi-replica data auditing with optimized metadata generation (CRMRDA). First, CRMRDA enhances replica generation efficiency by employing symmetric encryption and random masking. An indistinguishable challenge strategy is introduced, making the number of generated auditing metadata copies independent of the number of replicas. Second, we construct a security model for multi-replica data possession that allows server collusion and provide a formal security proof for CRMRDA. In addition, CRMRDA supports practical features such as dynamic operations and batch auditing. Finally, the efficiency of CRMRDA is evaluated in an experimental environment consisting of four servers, one third-party auditor, and one data owner. Compared to the latest multi-replica data auditing schemes, CRMRDA demonstrates lower computational overhead in replica generation, metadata generation, and periodic auditing.