Probing the Mystery of Cryptocurrency Theft: An Investigation into Methods for Taint Analysis

15 Pages Posted: 20 Jun 2019 Last revised: 24 Mar 2020

See all articles by Tin Tironsakkul

Tin Tironsakkul

Heriot-Watt University

Manuel Maarek

Heriot-Watt University

Andrea Eross

Heriot-Watt University

Mike Just

affiliation not provided to SSRN

Date Written: June 13, 2019

Abstract

Since the creation of Bitcoin, transaction tracking is one of the prominent means for following the movement of Bitcoins involved in illegal activities. Although every Bitcoin transaction is recorded in the blockchain ledger, which is transparent for anyone to observe and analyse, Bitcoin's pseudonymity system and transaction obscuring techniques still allow criminals to disguise their transaction trail. While there have been a few attempts to develop tracking methods, there is no accepted evaluation method to measure their accuracy. Therefore, this paper introduces a metrics-based evaluation framework to investigate the performance indicators of a theft transaction tracking. We use this framework to investigate strategies for transaction tracking. This paper also introduces two new tainting methods and an address profiling approach. We run an experiment to compare the accuracy of tainting strategies using data from real Bitcoin theft and a set of controls.

Keywords: Address Profiling, Cryptocurrency, Taint Analysis, Transaction Tracking

Suggested Citation

Tironsakkul, Tin and Maarek, Manuel and Eross, Andrea and Just, Mike, Probing the Mystery of Cryptocurrency Theft: An Investigation into Methods for Taint Analysis (June 13, 2019). Available at SSRN: https://ssrn.com/abstract=3403656 or http://dx.doi.org/10.2139/ssrn.3403656

Tin Tironsakkul (Contact Author)

Heriot-Watt University ( email )

Edinburgh
United Kingdom

Manuel Maarek

Heriot-Watt University ( email )

Andrea Eross

Heriot-Watt University ( email )

Mary Burton Building
School of Social Sciences
Edinburgh, Midlothian EH14 4AS
United Kingdom

Mike Just

affiliation not provided to SSRN

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