Construction of an economic data analysis and management system for legal regulation

This study addresses the efficiency limitations of traditional economic data analysis methods when processing large-scale, multi-source datasets under regulatory constraints. A blockchain-based system is proposed, featuring a novel sharding consensus algorithm with security and performance tradeoffs (SPTSCA) as its core component. Compared with existing approaches such as practical Byzantine fault tolerance (PBFT) and OmniLedger, the key innovations of SPTSCA include a dynamic shard adjustment mechanism for improved load balancing and an optimised consensus process that minimises communication rounds. Experimental results demonstrate that, due to more balanced shard formation, SPTSCA achieves up to a 1.49% increase in throughput compared with OmniLedger. More importantly, its performance significantly surpasses that of PBFT, with maximum throughput improvements of 143.1% and latency reductions of 89.1%. The algorithm enables secure large-scale economic data sharing, providing robust technical support for regulatory authorities.