A Decentralized Identity-based Cross-Domain Data Trading System

This paper presents a decentralized identity-based cross-domain data trading system designed to address identity inconsistency, service unavailability, transaction non-atomicity, and insufficient regulatory granularity in blockchain-enabled data markets. The proposed architecture introduces a unified decentralized identity layer for users and data assets, a secure cross-domain DID resolution protocol, a consistency-preserving cache, and an availability mechanism that combines consistent-hash-based scope allocation, redundancy, incentives, malicious-node detection, and punishment. On this basis, modular smart contracts implement cross-domain information verification, identity-attribute regulation, transaction validation, payment approval, and data transfer, while decentralized custody nodes and parallel transmission improve data delivery robustness. A prototype was deployed on 20 CentOS 7 servers divided into two blockchain domains, with each server equipped with an eight-core 2.4 GHz processor, 8 GB RAM, and 50 GB SSD storage. Experiments using 100,000 ERC-1056 DID records show that cache-free cross-domain resolution maintains complete consistency, while a 50% cache hit rate causes 14% of first-resolution results to require secondary resolution; the proposed update and re-resolution mechanisms restore full consistency and improve the effective hit rate by 72%. Even when the cache hit rate rises further, the initial inconsistency ratio increases only to 19%. Without caching, average cross-domain identity resolution latency is 180 ms, whereas LRU caching at a 70% hit rate reduces it to 82 ms, a 54.4% decrease. At a transaction submission rate of 500 tps, submitted transactions wait an average of 2.3 blocks, and two sequential smart-contract executions require approximately 5 s. With a gas limit of 10,000,000, the base blockchain throughput is about 200 tps, while fully cross-domain trading sustains approximately 90 tps. Raising the gas limit to 30,000,000 increases throughput from roughly 270 to 360 tps across the tested transaction-ratio range. These results demonstrate that the proposed system achieves secure, regulatable, consistent, and practically efficient cross-domain data trading at scale. A protocol-level Monte Carlo analysis further shows that, with eight voting edge nodes and dual-node cross-verification, the collusive false-acceptance upper bound is 0.522% at a 30% independent malicious-node probability; a separate consistent-hash simulation over 2-16 domains confirms logarithmic lookup growth and decreasing scope remapping as the network scales.