Abstract: With the rapid development of blockchain technology,illegal transactions with the help of virtual currencies are beco-ming increasingly common and still growing rapidly.In order to combat such crimes,blockchain transaction data are currently stu-died mainly from the perspectives of network analysis technology and graph data mining for blockchain transaction tracking.However,the existing studies are deficient in terms of effectiveness,generalizability,and efficiency,and cannot effectively track newly registered addresses.To address the above issues,a node-influence-based blockchain transaction tracking method NITT for account balance models is proposed in the paper,aiming to track the main fund flow of a specific target account model address.Compared with traditional methods,the proposed method introduces a temporal strategy to reduce the graph data size.It also filters out more influential and important account addresses by using a multiple weight assignment strategy.Experimental results on real datasets show that the proposed method has greater advantages in terms of effectiveness,generalizability and efficiency.

Key words: Blockchain, Anonymous transaction tracking, Account balance model, Node influence