On-chain analysis-based detection of abnormal transaction amount on cryptocurrency exchanges

【Author】 Gu, Zhuoming; Lin, Dan; Wu, Jiajing

【Source】PHYSICA A-STATISTICAL MECHANICS AND ITS APPLICATIONS

【影响因子】3.778

【Abstract】Cryptocurrency exchanges play an indispensable role in the cryptocurrency market. However, some exchanges are suspected to be involved in various abnormal or malicious behaviors while providing services to users, such as money laundering, wash trading and even running away. Besides, these behaviors are reported to be often accompanied by an anomalous increase in the transaction amount. Therefore, it is a topic worthy of study to detect whether the abnormal transaction amount occurs in the exchange and when it occurs. This paper uses web crawler tools to collect a relatively complete dataset of exchanges and then conducts a correlation analysis to obtain the most important factors that influence the transaction amount of different exchanges. Then, the prediction model of the influence of various factors on the transaction amount is obtained based on deep learning. The deviation between the predicting transaction amount and the actual transaction amount is calculated to provide a basis for abnormal transaction amount detection. Finally, through a case study on the detection results, some abnormal transaction amounts are related to policy changes and industry events, while the others are suspected to be related to illegal behaviors. (C) 2022 Elsevier B.V. All rights reserved.

【Keywords】Blockchain; Cryptocurrency; Exchange; Anomaly detection

【发表时间】2022 15-Oct

【收录时间】2022-08-15

【文献类型】实证数据

【主题类别】

区块链治理-技术治理-异常/非法交易识别