PACIS 2022 Proceedings

Paper Number

1293

Abstract

The anonymity of Bitcoin is always accompanied with illegal transactions and criminals’ evasion of legal prosecution. Furthermore, the recent introduction of a mixing service, an anonymous enhancement technology, has intensified the difficulty of analyzing user identity by using traditional methods. Actually, Bitcoin historical transactions are open and traceable. Therefore, these can be used to identify trading entities participating in mixing services. In this paper, we formally describe the mechanism of mixing services and the discovery of its correlation with circular trading. Then, a graph-clustering-based transaction network analysis algorithm is proposed to complete the detection of transaction cycles through three steps: address clustering, transaction graph construction and cycle detection. Through experiments with 1,500,000 real transaction records, we verify the correlation between the mixing service and circular transactions and the validity of the proposed detection algorithm. The work provides a basis for the regulatory authorities to crack down on illegal trading.

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