| Since the birth of bitcoin,after more than ten years of development,both the bitcoin cryptocurrency itself and its application of blockchain technology have attracted widespread attention.Bitcoin's peer-to-peer decentralization has attracted more and more people to the bitcoin network,making its ever-increasing volume of transaction data a valuable resource for studying the currency.The bitcoin network has become a haven for criminals and illegal transactions because of the anonymity that people use for transactions that are unrelated to their identity.But there is no denying that bitcoin transaction data contains huge value,waiting for people to dig and explore.Therefore,this paper will analyze and study the transaction data in the bitcoin network.First of all,this paper introduces the development background of bitcoin,elaborates the related principles of bitcoin and the transaction process of bitcoin.Then it introduces the structure of bitcoin transaction data,studies the relevant literature on the analysis of bitcoin transaction data in recent years,and summarizes the analysis technology and research direction of bitcoin transaction data.Secondly,In order to better study the entity characteristics of bitcoin transaction data,this paper designs HIER,the incremental entity recognition scheme of bitcoin transaction data,and elaborates the overall architecture design and the core processing flow of the key modules of the scheme.The HIER scheme improves the inefficient of traditional heuristic entity identification methods by building a set of entity relationships and adopting active address data.In this paper,the performance of HIER scheme is theoretically analyzed and discussed,and the performance of HIER scheme is verified by experiments.Finally,the paper dynamically studies the changes of Bitcoin transaction data according to the incremental way,and analyzes the characteristics of Bitcoin transaction data.Finally,since there are many illegal behaviors in the bitcoin network,this paper proposes an analysis model MTE for the characteristics of illegal behaviors in the bitcoin transaction data.Firstly,it gives a brief overview of illegal behaviors in the bitcoin network and it's detection methods.Then,it introduces the overall design idea of the MTE model,and carries out different analyses from the two aspects of illegal transactions and illegal entities.Each level of analysis is introduced from several stages,such as data source,network construction,feature extraction and analysis method.Finally,the validity of the model is verified by analyzing the bitcoin transaction data through experiments and the characteristics of illegal behavior are summarized. |
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