Automatic Bitcoin Address Clustering
- 1 December 2017
- conference paper
- conference paper
- Published by Institute of Electrical and Electronics Engineers (IEEE)
- p. 461-466
- https://doi.org/10.1109/icmla.2017.0-118
Abstract
Bitcoin is digital assets infrastructure powering the first worldwide decentralized cryptocurrency of the same name. All history of Bitcoins owning and transferring (addresses and transactions) is available as a public ledger called blockchain. But real-world owners of addresses are not known in general. That's why Bitcoin is called pseudo-anonymous. However, some addresses can be grouped by their ownership using behavior patterns and publicly available information from off-chain sources. Blockchain-based common behavior pattern analysis (common spending and one-time change heuristics) is widely used for Bitcoin clustering as votes for addresses association, while offchain information (tags) is mostly used to verify results. In this paper, we propose to use off-chain information as votes for address separation and to consider it together with blockchain information during the clustering model construction step. Both blockchain and off-chain information are not reliable, and our approach aims to filter out errors in input data. The results of the study show the feasibility of a proposed approached for Bitcoin address clustering. It can be useful for the users to avoid insecure Bitcoin usage patterns and for the investigators to conduct a more advanced de-anonymizing analysis.Keywords
This publication has 12 references indexed in Scilit:
- A STATISTICAL RISK ASSESSMENT OF BITCOIN AND ITS EXTREME TAIL BEHAVIORAnnals of Financial Economics, 2017
- Behavior pattern clustering in blockchain networksMultimedia Tools and Applications, 2017
- Bitcoin over Tor isn't a Good IdeaPublished by Institute of Electrical and Electronics Engineers (IEEE) ,2015
- BitIodine: Extracting Intelligence from the Bitcoin NetworkPublished by Springer Science and Business Media LLC ,2014
- Towards Risk Scoring of Bitcoin TransactionsPublished by Springer Science and Business Media LLC ,2014
- Evaluating User Privacy in BitcoinLecture Notes in Computer Science, 2013
- An Analysis of Anonymity in the Bitcoin SystemPublished by Institute of Electrical and Electronics Engineers (IEEE) ,2011
- Community detection in graphsPhysics Reports, 2009
- Unsupervised LearningLecture Notes in Computer Science, 2004
- Data clusteringACM Computing Surveys, 1999