Fine-grained Verifiable Data Query for Multi-SPs in Hybrid-Storage Blockchain

As the amount of data generated by terminal devices continues to increase, the data owner (DO) often outsources data to the service provider (SP) to mitigate the burden on local storage and computing resources. Since the physical control of data is transferred to semi-trusted cloud service provider, the outsourced data becomes vulnerable to tampering or damage. Hybrid-storage blockchain is a promising solution for distributed and secure data storage. However, considering that DO may outsource data to multi-SPs in actual scenarios, the current verification scheme is inadequate for supporting fine-grained verifiable queries. The user is unable to discern which data from which SP in the query result has been forged or omitted, and can only receive all or discard all, resulting in huge re-query and transmission costs. First, we propose the fine-grained verifiable data query (FVDQ) scheme, which organizes data into a matrix or cube form, constructs row and column (face) digests using vector commitments and accumulators, and verifies these digests to pinpoint the location of tampered or omitted data. Furthermore, we propose FVDQ for multi-SPs (FVDQ4M), which extends the fine-grained verifiable query approach to multi-SPs environments. By constructing hierarchical vector commitments, FVDQ4M enables users to identify the SP from which the forged results come from. Finally, we present an efficiency-optimized FVDQ4M+ scheme, which reduces on-chain storage costs and off-chain redundant queries, and achieves enhanced query efficiency by digest aggregation and bloom filter-based routing mechanism. Experimental results show that compared with the baseline scheme, our scheme takes less VO construction time and verification time.