Abstract
The Bisq trade protocol is a key component of the Bisq decentralised exchange, allowing users to trade with one another in a decentralised manner. However, the protocol publishes trade data to the Bitcoin blockchain. In this paper, we analyse the privacy risks this creates for users. Specifically, we present two new heuristics, one to identify Bisq trades on the Bitcoin blockchain and another to cluster the addresses used in those trades. We demonstrate that these heuristics are effective in identifying the trading activity of Bisq users and aggregating their trading activity across multiple trades. We conclude with suggestions as to how best to defeat these heuristics and improve the privacy aspects of the Bisq trade protocol.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Similar content being viewed by others
Notes
- 1.
- 2.
Source code implementing both heuristics can be found here: https://github.com/Liam-Hickey-Ire/BisqTradeProtocolAnalysisSource.
- 3.
https://github.com/Liam-Hickey-Ire/BisqTradeProtocolAnalysisSource/blob/master/Data/670026/our-deposit-tx-hashes.csv: This CSV file lists the deposit transaction hashes of every trade identified by our heuristic.
- 4.
Protocol Buffers is a data serialisation mechanism developed by Google, similar in function to other data serialisation mechanisms such as JSON or XML.
- 5.
https://github.com/Liam-Hickey-Ire/BisqTradeProtocolAnalysisSource/blob/master/Data/670026/bisq-deposit-tx-hashes.csv: Each line of this CSV file lists the deposit transaction hashes of every Bisq trade retrieved from TradeStatistics2, with corrupted and duplicate entries removed.
- 6.
References
Adams, H., Zinsmeister, N., Robinson, D.: Uniswap V2 core, March 2020. https://uniswap.org/whitepaper.pdf
Bisq network documentation. https://docs.bisq.network
Harrigan, M., Fretter, C.: The unreasonable effectiveness of address clustering. In: The IEEE International Conference on Advanced and Trusted Computing (ATC), pp. 368–373. IEEE Computer Society (2016)
Hickey, L., Harrigan, M.: The Bisq DAO: on the privacy cost of participation. In: IEEE Symposium on Computers and Communications (2020)
Huang, D.Y., et al.: Tracking ransomware end-to-end. In: The IEEE Symposium on Security and Privacy, pp. 618–631. IEEE (2018)
Jourdan, M., Blandin, S., Wynter, L., Deshpande, P.: Characterizing entities in the Bitcoin blockchain. In: The International Workshop on Blockchain and Sharing Economy Applications (BlockSEA 2018) at the IEEE International Conference on Data Mining (ICDM). IEEE (2018)
Lin, L.X.: Deconstructing decentralized exchanges (2019). https://stanford-jblp.pubpub.org/pub/deconstructing-dex
Maesa, D.D.F., Marino, A., Ricci, L.: Data-driven analysis of bitcoin properties: exploiting the users graph. Int. J. Data Sci. Anal. 6, 63–80 (2018)
Meiklejohn, S., et al.: A fistful of bitcoins: characterizing payments among men with no names. Commun. ACM (CACM) 59(4), 86–93 (2016)
Möser, M., et al.: An empirical analysis of traceability in the Monero blockchain. In: Proceedings on Privacy Enhancing Technologies, pp. 143–163 (2018). https://doi.org/10.1515/popets-2018-0025
Nick, J.: Data-driven de-anonymization in Bitcoin. Master’s thesis, ETH Zürich (2015)
Nieves, P.: Identification of cross blockchain transactions: a feasibility study. Master’s thesis, Technical University of Munich (2018)
Quesnelle, J.: On the linkability of Zcash transactions (2017). https://arxiv.org/abs/1712.01210
Rosenfeld, M.: Overview of colored coins (2012). https://bitcoil.co.il/BitcoinX.pdf
THORChain: A decentralised liquidity network. https://github.com/thorchain/Resources/tree/master/Whitepapers
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2022 Springer Nature Switzerland AG
About this paper
Cite this paper
Hickey, L., Harrigan, M. (2022). Decentralisation over Privacy: An Analysis of the Bisq Trade Protocol. In: Chaves, R., et al. Euro-Par 2021: Parallel Processing Workshops. Euro-Par 2021. Lecture Notes in Computer Science, vol 13098. Springer, Cham. https://doi.org/10.1007/978-3-031-06156-1_17
Download citation
DOI: https://doi.org/10.1007/978-3-031-06156-1_17
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-031-06155-4
Online ISBN: 978-3-031-06156-1
eBook Packages: Computer ScienceComputer Science (R0)