Research And Implementation Of Cryptocurrency Label Library System

Blockchain-based cryptocurrency has developed rapidly in recent years,and the scale of transactions has continued to rise.However,due to the decentralized nature and a certain degree of anonymity of blockchain cryptocurrency,it has become an important tool for criminals to conduct illegal transactions.Criminals use blockchain cryptocurrency to carry out illegal activities such as dark web black market transactions,ransomware attacks,fraud,money laundering,etc.According to data from blockchain research organization Chainalysis,crimes involving cryptocurrency reached 20.6 billion US dollars in 2022.The number of illegal bitcoin transactions is still expanding,so it is imperative to conduct research on transaction traceability of Bitcoin and other blockchain-based encrypted cryptocurrencies,so as to locate the identity information of illegal traders,track the flow of funds,and curb the Illegal and criminal acts of blockchain cryptocurrency.This work is mainly aimed at labeling blockchain cryptocurrency transaction addresses.Currently,existing research cannot fully and accurately label cryptocurrency addresses.There are a large number of label conflicts,label errors,and label missing issues,which need to be studied.The main work and research contents of the thesis are as follows:(1)Aiming at the label conflict problem,this paper proposes an address label conflict resolution method based on a multi-dimensional label system.Firstly,a multi-dimensional label system is designed,and then the label conflicts in different situations are analyzed.The label conflict of the label address is classified and identified,and finally the method of combining the truth discovery algorithm with the Bitcoin address clustering heuristic is used to identify the correct address label among the conflicting labels and realize conflict resolution.Experimental results show that this method can accurately resolve Bitcoin multi-label conflicts.(2)Aiming at the problem of incomplete information collection and manual input of labels,this paper proposes an event-based intelligent automatic labeling method.Firstly,the transaction-related entities and relationships in news events are automatically extracted through entity recognition and relationship extraction algorithms,and then the belonging relationships are identified,so as to automatically label the addresses contained therein.Experimental results show that this method can extract address tags from unstructured information accurately.(3)This paper designs and implements a blockchain cryptocurrency tag library system,which collects block and transaction information on a variety of cryptocurrency blockchains,and integrates the blockchain digital currency address tag information of more than ten intelligence websites and social platforms.The system has realized various functions such as on-chain data collection,label incremental collection,address incremental clustering,address multi-dimensional labeling,and digital currency transaction entity database.The system has a friendly user interaction interface and supports users to trace the identity of blockchain encrypted digital currency addresses.