A Verifiable and Low-Latency Cross-Chain IoT Service Query Scheme with Collaborative Indexing

Internet of Things (IoT) devices are widely used and pervasive, commonly collecting daily life data and often involving personal information. The sensitivity of the data brings security concerns when handling it. Blockchain ensures decentralization and data security through immutable service records and tamper-proof query execution. The single-chain architecture is constrained in supporting multi-agency IoT environments for isolated data structures and interoperability bottlenecks. On the other hand, cross-chain service queries enable secure interoperability and dynamic resource integration across heterogeneous blockchain systems, but are amenable to privacy breaches, query latency, and consistency in multi-chain environments. To address these challenges, we propose a verifiable and low-latency cross-chain IoT service query scheme with the collaborative indexing. To encapsulate IoT service attributes, we design a service metadata model based on partial homomorphic encryption, allowing service providers to upload services without revealing the private service information. To achieve fine-grained metadata queries, the collaborative indexing mechanism filters irrelevant chains through a global index to narrow the query scope and then utilizes localized sub-indexes, optimizing search efficiency. Finally, we construct data structures based on fingerprint verification to ensure consistency between the query layer and blockchain data. We provide a security analysis of the robustness and privacy, and develop a supporting tool named ServChain. Experimental results demonstrate that, even with consistency verification, our scheme outperforms state-of-the-art solutions by significantly reducing query time (by at least 68.18%), communication overhead (by 45.9%), and computational cost (by 46.5% ).