Abstract: The existing blockchain system mostly adopts the equal mining mode.All bookkeepers (entities) record the books on a single main chain,and the data storage is random.Moreover,in complex or classified financial scenarios,the data of the main chain is difficult to realize association or regular storage,leading to low storage and query efficiency.At the same time,most event traceability in the existing blockchain system can only query the source block,and the implied association between entities cannot be identified,so the query has limitations.To solve these problems,composite blockchain associated event tracing method is proposed.Firstly,the composite chain storage structure model of blockchain is constructed,and the concepts of private chain and al-liance chain are proposed to realize the adaptive data association storage under complex or classified scenarios.Then,in the traceability query,on the basis of obtaining the event source entity block,the auxiliary storage space is set up to transfer the relevant data.A tracing method of the associated entity block based on the Apriori algorithm is proposed,and then the obtained traceability entity block is constructed as the source event correlation graph to describe the correlation relationship between the event entities.Finally,the risk assessment system based on reinforcement learning is proposed to realize the traceability entity risk assessment.Experiments show that the composite blockchain associated event tracing method can reduce the storage overhead by 60%,improve the query accuracy by 90% and improve security by 50%.

Key words: Alliance chain, Associated event tracing, Composite chain structure, Private chain, Reinforcement learning