Abstract
Address clustering tries to break the privacy of bitcoin users by linking all addresses created by an individual user, based on information available from the blockchain. As an alternative information source, observations of the underlying peer-to-peer network have also been used to attack the privacy of users. In this paper, we assess whether combining blockchain and network information may facilitate the clustering process. For this purpose, we apply all applicable clustering heuristics that are known to us to current blockchain information and associate the resulting clusters with IP address information extracted from observing the message flooding process of the bitcoin network. The results indicate that only a small share of clusters (less than 8%) were conspicuously associated with a single IP address. Also, only a small number of IP addresses showed a conspicuous association with a single cluster.
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Notes
- 1.
According to our measurements (http://dsn.tm.kit.edu/bitcoin), there are \(\approx \)4,200 peers reachable via IPv4 and an additional \(\approx \)1,500 peers reachable via IPv6. As we do not know how many peers are dual-stacked (reachable via IPv4 and IPv6), we cannot directly determine the exact number of reachable peers.
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Acknowledgement
This work was supported by the German Federal Ministry of Education and Research (BMBF) within the project \({KASTEL\_IoE}\) in the Competence Center for Applied Security Technology (KASTEL). The authors acknowledge the use of the InstitutsCluster II at the Steinbuch Centre for Computing, and would like to thank the anonymous reviewers for their valuable comments and suggestions.
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Figures 4 and 5 show a comparison of the resulting cluster sizes for all discussed clustering heuristics and various parameterizations of the growth based heuristic HG. For all heuristics, the cluster sizes roughly follow a power-law distribution.
Histogram of the number of clusters for various sizes (i.e., number of addresses per cluster).
Histogram of the number of clusters for various sizes (i.e., number of addresses per cluster).
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Neudecker, T., Hartenstein, H. (2017). Could Network Information Facilitate Address Clustering in Bitcoin?. In: Brenner, M., et al. Financial Cryptography and Data Security. FC 2017. Lecture Notes in Computer Science(), vol 10323. Springer, Cham. https://doi.org/10.1007/978-3-319-70278-0_9
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