Identification of High Yielding Investment Programs in Bitcoin via Transactions Pattern Analysis

Kentaroh Toyoda, Tomoaki Ohtsuki, P. Takis Mathiopoulos

Research output: Chapter in Book/Report/Conference proceedingConference contribution

11 Citations (Scopus)

Abstract

Although Bitcoin is one of the most successful decentralized cryptocurrency, recent research has revealed that it can be used as fraudulent activities such as HYIP (High Yield Investment Program). To identify such undesired activities, it is important to obtain Bitcoin addresses related with fraud. So far, the identification of such activities is based upon relating Bitcoin addresses with graph mining procedures. In this paper, we follow a different approach for identifying Bitcoin addresses related with HYIP by analyzing transactions patterns. In particular, based on the individual inspection of HYIP activity in Bitcoin, we propose a number of features that can be extracted from transactions. In particular, a signed integer called pattern is assigned to each transaction and the frequency of each pattern is calculated as key features. By evaluating the classification performance with more than 1,500 labeled Bitcoin addresses, it is shown that about 83% of HYIP addresses are correctly classified while maintaining false positive rate less than 4.4%.

Original languageEnglish
Title of host publication2017 IEEE Global Communications Conference, GLOBECOM 2017 - Proceedings
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages1-6
Number of pages6
ISBN (Electronic)9781509050192
DOIs
Publication statusPublished - 2017 Jul 1
Event2017 IEEE Global Communications Conference, GLOBECOM 2017 - Singapore, Singapore
Duration: 2017 Dec 42017 Dec 8

Publication series

Name2017 IEEE Global Communications Conference, GLOBECOM 2017 - Proceedings
Volume2018-January

Other

Other2017 IEEE Global Communications Conference, GLOBECOM 2017
CountrySingapore
CitySingapore
Period17/12/417/12/8

ASJC Scopus subject areas

  • Computer Networks and Communications
  • Hardware and Architecture
  • Safety, Risk, Reliability and Quality

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    Toyoda, K., Ohtsuki, T., & Mathiopoulos, P. T. (2017). Identification of High Yielding Investment Programs in Bitcoin via Transactions Pattern Analysis. In 2017 IEEE Global Communications Conference, GLOBECOM 2017 - Proceedings (pp. 1-6). [8254420] (2017 IEEE Global Communications Conference, GLOBECOM 2017 - Proceedings; Vol. 2018-January). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/GLOCOM.2017.8254420