Time series analysis for bitcoin transactions: The case of Pirate@40's HYIP scheme

Kentaro Toyoda, Tomoaki Ohtsuki, P. Takis Mathiopoulos

研究成果: Conference contribution

抄録

Due to the increased popularity of Bitcoin, many researchers have analyzed how Bitcoin is being used based on the transaction history. However, the existing works analyze the transaction history in a 'static' manner and none of them analyzes transaction history 'dynamically', i.e. without taking into account the 'time variation of how Bitcoin is transferred'. The time analysis is in great demand for many practical cases, such as digital forensics tool that infers what was going on behind the scene of a fraudulent scam, and real-time inference of marketplace sales. In this paper, we propose a novel time series analysis for analyzing the history of Bitcoin transactions. In fact the main goal of our research is to detect changing points, namely anomaly detection, against a given (Bitcoin) address's transaction history. To show the effectiveness of the proposed approach, it is tested against the transaction history of Pirate@40's HYIP (High Yielding Investment Program) scheme, which raised 700,000 BTC from his investors and was charged by the Security and Exchange Commission (SEC) in 2013. It is shown that the proposed approach can successfully detect several remarkable points of Pirate@40's HYIP scheme, such as when its program's name was changed to Bitcoin Saving & Trust and when its investment rule was changed.

本文言語English
ホスト出版物のタイトルProceedings - 18th IEEE International Conference on Data Mining Workshops, ICDMW 2018
編集者Jeffrey Yu, Zhenhui Li, Hanghang Tong, Feida Zhu
出版社IEEE Computer Society
ページ151-155
ページ数5
ISBN(電子版)9781538692882
DOI
出版ステータスPublished - 2019 2 7
イベント18th IEEE International Conference on Data Mining Workshops, ICDMW 2018 - Singapore, Singapore
継続期間: 2018 11 172018 11 20

出版物シリーズ

名前IEEE International Conference on Data Mining Workshops, ICDMW
2018-November
ISSN(印刷版)2375-9232
ISSN(電子版)2375-9259

Conference

Conference18th IEEE International Conference on Data Mining Workshops, ICDMW 2018
CountrySingapore
CitySingapore
Period18/11/1718/11/20

ASJC Scopus subject areas

  • Computer Science Applications
  • Software

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