Exploring Unconfirmed Transactions for Effective Bitcoin Address Clustering
Authors: 
Kai Wang, Yakun Cheng, Michael Wen Tong, Zhenghao Niu, Jun Pang, 
Weili HanAuthors Info & Claims
Kai Wang, Yakun Cheng, Michael Wen Tong, Zhenghao Niu, Jun Pang, Weili HanAuthors Info & ClaimsPages 1880 - 1891
Abstract
The advancement of clustering heuristics has demonstrated that the addresses of Bitcoin, which are protected by their anonymous mechanisms, can be de-anonymized. While the state-of-the-art (SOTA) clustering heuristics focus on confirmed transactions stored in the blockchain, they ignore unconfirmed transactions in the mempool. These unconfirmed transactions contain information about transactions before being stored in the blockchain, covering additional address associations that can improve Bitcoin address clustering.
In this paper, we bridge the gap by combining confirmed and unconfirmed transactions for effective Bitcoin address clustering. First, we introduce a reliable data collection framework to collect both confirmed and unconfirmed Bitcoin transactions. Second, we propose two novel clustering heuristics that exploit specific behavior patterns in unconfirmed transactions and uncover additional address associations. Finally, we construct a labeled dataset and experimentally show that the effectiveness of our proposed clustering heuristics, improving recall by at least three times with higher precision compared to the SOTA clustering heuristics. Our findings show the value of unconfirmed transactions for Bitcoin address clustering and further reveal the challenges of achieving anonymity in Bitcoin. To the best of our knowledge, our study is the first to explore unconfirmed transactions for Bitcoin address clustering.
Supplemental Material
MP4 File
video presentation
- Download
- 1179.91 MB
MP4 File
Supplemental video
- Download
- 38.75 MB
References
[1]
Elli Androulaki, Ghassan Karame, Marc Roeschlin, Tobias Scherer, and Srdjan Capkun. 2013. Evaluating User Privacy in Bitcoin. In Proceedings of the 17th International Conference on Financial Cryptography and Data Security (FC) (Lecture Notes in Computer Science, Vol. 7859). Springer, 34--51.
[2]
Ré my Cazabet, Rym Baccour, and Matthieu Latapy. 2017. Tracking Bitcoin Users Activity Using Community Detection on a Network of Weak Signals. In Proceedings of the 6th International Conference on Complex Networks and Their Applications (Complex Networks) (Studies in Computational Intelligence, Vol. 689). Springer, 166--177.
[3]
Chainalysis. 2022. Chainalysis: The Blockchain Data Platform. https://www.chainalysis.com/.
[4]
Mauro Conti, Sandeep Kumar E, Chhagan Lal, and Sushmita Ruj. 2018. A Survey on Security and Privacy Issues of Bitcoin. IEEE Communications Surveys & Tutorials, Vol. 20, 4 (2018), 3416--3452.
[5]
Jesse Dunietz. 2017. The Imperfect Crime: How the WannaCry Hackers Could Get Nabbed. https://www.scientificamerican.com/article/the-imperfect-crime-how-the-wannacry-hackers-could-get-nabbed.
[6]
Dmitry Ermilov, Maxim Panov, and Yury Yanovich. 2017. Automatic Bitcoin Address Clustering. In Proceedings of 16th International Conference on Machine Learning and Applications (ICMLA). IEEE, 461--466.
[7]
Steven Goldfeder, Harry A. Kalodner, Dillon Reisman, and Arvind Narayanan. 2018. When the cookie meets the blockchain: Privacy risks of web payments via cryptocurrencies. Proceedings on Privacy Enhancing Technologies, Vol. 2018, 4 (2018), 179--199.
[8]
Yanan Gong, Kam-Pui Chow, Hing-Fung Ting, and Siu-Ming Yiu. 2022. Analyzing the Error Rates of Bitcoin Clustering Heuristics. In Proceedings of the 2022 International Conference on Advances in Digital Forensics (IFIP) (IFIP Advances in Information and Communication Technology, Vol. 653). Springer, 187--205.
[9]
Andy Greenberg. 2021. Prosecutors Trace $13.4M in Bitcoins From the Silk Road to Ulbricht's Laptop. https://www.wired.com/2015/01/prosecutors-trace-13--4-million-bitcoins-silk-road-ulbrichts-laptop.
[10]
Rowel Gü ndlach, Martijn Gijsbers, David T. Koops, and Jacques Resing. 2021. Predicting confirmation times of Bitcoin transactions. ACM SIGMETRICS Performance Evaluation Review, Vol. 48, 4 (2021), 16--19.
[11]
David A. Harding and Peter Todd. 2015. Opt-in Full Replace-by-Fee Signaling. https://github.com/bitcoin/bips/blob/master/bip-0125.mediawiki.
[12]
Martin Harrigan and Christoph Fretter. 2016. The Unreasonable Effectiveness of Address Clustering. In Proceedings of the 2016 International Conference on Ubiquitous Intelligence & Computing, Advanced and Trusted Computing, Scalable Computing and Communications, Cloud and Big Data Computing, Internet of People, and Smart World Congress (UIC/ATC/ScalCom/CBDCom/IoP/SmartWorld). IEEE, 368--373.
[13]
Danny Yuxing Huang, Maxwell Matthaios Aliapoulios, Vector Guo Li, Luca Invernizzi, Elie Bursztein, Kylie McRoberts, Jonathan Levin, Kirill Levchenko, Alex C. Snoeren, and Damon McCoy. 2018. Tracking Ransomware End-to-end. In Proceedings of the 39th IEEE Symposium on Security and Privacy (S&P). IEEE, 618--631.
[14]
Danny Yuxing Huang, Hitesh Dharmdasani, Sarah Meiklejohn, Vacha Dave, Chris Grier, Damon McCoy, Stefan Savage, Nicholas Weaver, Alex C. Snoeren, and Kirill Levchenko. 2014. Botcoin: Monetizing Stolen Cycles. In Proceedings of the 21st Annual Network and Distributed System Security Symposium (NDSS). The Internet Society.
[15]
Blockchain.com Inc. 2022. The world's most popular way to buy, sell, and trade crypto. https://www.blockchain.com/.
[16]
Harshal Shridhar Kallurkar and B. R. Chandavarkar. 2022. Unconfirmed Transactions in Cryptocurrency: Reasons, Statistics, and Mitigation. In Proceedings of 2022 International Conference on Public Key Infrastructure and its Applications (PKIA). IEEE, 1--7.
[17]
Harry A. Kalodner, Malte Mö ser, Kevin Lee, Steven Goldfeder, Martin Plattner, Alishah Chator, and Arvind Narayanan. 2020. BlockSci: Design and applications of a blockchain analysis platform. In Proceedings of the 29th USENIX Security Symposium (USENIX Security). USENIX Association, 2721--2738.
[18]
George Kappos, Haaroon Yousaf, Rainer Stü tz, Sofia Rollet, Bernhard Haslhofer, and Sarah Meiklejohn. 2022. How to Peel a Million: Validating and Expanding Bitcoin Clusters. In Proceedings of the 31th USENIX Security Symposium (USENIX security). USENIX Association, 2207--2223.
[19]
Dae-Yong Kim, Meryam Essaid, and Hongtaek Ju. 2020. Examining Bitcoin mempools Resemblance Using Jaccard Similarity Index. In Proceedings of the 21st Asia-Pacific Network Operations and Management Symposium (APNOMS). IEEE, 287--290.
[20]
Kyungchan Ko, Taeyeol Jeong, Sajan Maharjan, Chaehyeon Lee, and James Won-Ki Hong. 2019. Prediction of Bitcoin Transactions Included in the Next Block. In Proceedings of the 1st International Conference on Blockchain and Trustworthy Systems (BlockSys) (Communications in Computer and Information Science, Vol. 1156). Springer, 591--597.
[21]
Yang Li, Zilu Liu, and Zibin Zheng. 2019. Quantitative Analysis of Bitcoin Transferred in Bitcoin Exchange. In Proceedings of the 1st International Conference on Blockchain and Trustworthy Systems (BlockSys) (Communications in Computer and Information Science, Vol. 1156). Springer, 549--562.
[22]
Kevin Liao, Ziming Zhao, Adam Doupé, and Gail-Joon Ahn. 2016. Behind closed doors: measurement and analysis of CryptoLocker ransoms in Bitcoin. In Proceedings of the 2016 APWG Symposium on Electronic Crime Research (eCrime). IEEE, 1--13.
[23]
Feng Liu, Zhihan Li, Kun Jia, Panwei Xiang, Aimin Zhou, Jiayin Qi, and Zhibin Li. 2023. Bitcoin Address Clustering Based on Change Address Improvement. IEEE Transactions on Computational Social Systems (2023), 1--12.
[24]
Eric Lombrozo, Johnson Lau, and Pieter Wuille. 2015. Segregated Witness (Consensus layer). https://github.com/bitcoin/bips/blob/master/bip-0141.mediawiki.
[25]
Greg Maxwell. 2013. CoinJoin: Bitcoin privacy for the real world. https://bitcointalk.org/index.php?topic=279249.
[26]
Sarah Meiklejohn, Marjori Pomarole, Grant Jordan, Kirill Levchenko, Damon McCoy, Geoffrey M. Voelker, and Stefan Savage. 2013. A fistful of bitcoins: characterizing payments among men with no names. In Proceedings of the 2013 Internet Measurement Conference (IMC). ACM, 127--140.
[27]
Malte Mö ser and Arvind Narayanan. 2022. Resurrecting Address Clustering in Bitcoin. In Proceedings of the 26th International Conference on Financial Cryptography and Data Security (FC) (Lecture Notes in Computer Science, Vol. 13411). Springer, 386--403.
[28]
Satoshi Nakamoto. 2009. Bitcoin: A peer-to-peer electronic cash system. https://bitcoin.org/bitcoin.pdf
[29]
Jonas David Nick. 2015. Data-Driven De-Anonymization in Bitcoin. In Master's thesis. ETH Zürich.
[30]
United States Department of Justice. 2020. Global Disruption of Three Terror Finance Cyber-Enabled Campaigns. https://www.justice.gov/opa/pr/global-disruption-three-terror-finance-cyber-enabled-campaigns.
[31]
OrdinalHub.com. 2023. Discover, Track & Analyze Bitcoin Ordinals. https://www.ordinalhub.com/.
[32]
Masarah Paquet-Clouston, Bernhard Haslhofer, and Benoit Dupont. 2019a. Ransomware payments in the Bitcoin ecosystem. Journal of Cybersecurity, Vol. 5, 1 (2019), tyz003.
[33]
Masarah Paquet-Clouston, Matteo Romiti, Bernhard Haslhofer, and Thomas Charvat. 2019b. Spams meet Cryptocurrencies: Sextortion in the Bitcoin Ecosystem. In Proceedings of the 1st ACM Conference on Advances in Financial Technologies (AFT). ACM, 76--88.
[34]
Rebecca S. Portnoff, Danny Yuxing Huang, Periwinkle Doerfler, Sadia Afroz, and Damon McCoy. 2017. Backpage and Bitcoin: Uncovering Human Traffickers. In Proceedings of the 23rd International Conference on Knowledge Discovery and Data Mining (SIGKDD). ACM, 1595--1604.
[35]
Fergal Reid and Martin Harrigan. 2011. An Analysis of Anonymity in the Bitcoin System. In Proceedings of the 2nd International Conference on Privacy, Security, Risk and Trust (PASSAT). IEEE, 1318--1326.
[36]
Casey Rodarmor. 2022. Ordinal Numbers. https://github.com/ordinals/ord/blob/master/bip.mediawiki.
[37]
Muhammad Saad, Laurent Njilla, Charles A. Kamhoua, Joongheon Kim, DaeHun Nyang, and Aziz Mohaisen. 2019. Mempool optimization for Defending Against DDoS Attacks in PoW-based Blockchain Systems. In Proceedings of the 2019 International Conference on Blockchain and Cryptocurrency (ICBC). IEEE, 285--292.
[38]
Muhammad Saad, My T. Thai, and Aziz Mohaisen. 2018. POSTER: Deterring DDoS Attacks on Blockchain-based Cryptocurrencies through Mempool Optimization. In Proceedings of the 2018 on Asia Conference on Computer and Communications Security (AsiaCCS). ACM, 809--811.
[39]
Michele Spagnuolo, Federico Maggi, and Stefano Zanero. 2014. BitIodine: Extracting Intelligence from the Bitcoin Network. In Proceedings of the 18th International Conference on Financial Cryptography and Data Security (FC) (Lecture Notes in Computer Science, Vol. 8437). Springer, 457--468.
[40]
Ivo Stoepker, Rowel Gü ndlach, and Stella Kapodistria. 2021. Robustness analysis of Bitcoin confirmation times. ACM SIGMETRICS Performance Evaluation Review, Vol. 48, 4 (2021), 20--23.
[41]
Kai Wang, Jun Pang, Dingjie Chen, Yu Zhao, Dapeng Huang, Chen Chen, and Weili Han. 2022. A Large-scale Empirical Analysis of Ransomware Activities in Bitcoin. ACM Transactions on the Web, Vol. 16, 2 (2022), 7:1--7:29.
[42]
Qin Wang and Guangsheng Yu. 2023. Understanding BRC-20: Hope or Hype. (2023).
[43]
Yunpeng Wang, Jin Yang, Tao Li, Fangdong Zhu, and Xiaojun Zhou. 2018. Anti-dust: A method for identifying and preventing Blockchain's dust attacks. In Proceedings of the 2018 International Conference on Information Systems and Computer Aided Education (ICISCAE). IEEE, 274--280.
[44]
Pieter Wuille, Jonas Nick, and Anthony Towns. 2020. Taproot: SegWit version 1 spending rules. https://github.com/bitcoin/bips/blob/master/bip-0341.mediawiki.
[45]
Haaroon Yousaf, George Kappos, and Sarah Meiklejohn. 2019. Tracing Transactions Across Cryptocurrency Ledgers. In Proceedings of the 28th USENIX Security Symposium (USENIX Security). USENIX Association, 837--850.
[46]
Limeng Zhang, Rui Zhou, Qing Liu, Jiajie Xu, and Chengfei Liu. 2021. Transaction Confirmation Time Estimation in the Bitcoin Blockchain. In Proceedings of the 22nd International Conference on Web Information Systems Engineering (WISE) (Lecture Notes in Computer Science, Vol. 13080). Springer, 30--45.
[47]
Limeng Zhang, Rui Zhou, Qing Liu, Jiajie Xu, and Chengfei Liu. 2022. Bitcoin Transaction Confirmation Time Prediction: A Classification View. In Proceedings of the 23rd International Conference on Web Information Systems Engineering (WISE) (Lecture Notes in Computer Science, Vol. 13724). Springer, 155--169.
[48]
Baokun Zheng, Liehuang Zhu, Meng Shen, Xiaojiang Du, and Mohsen Guizani. 2020. Identifying the vulnerabilities of bitcoin anonymous mechanism based on address clustering. Science China Information Sciences, Vol. 63, 3 (2020), 1--15.
Index Terms
- Exploring Unconfirmed Transactions for Effective Bitcoin Address Clustering
Recommendations
Bitcoin user analysis based on address clustering and community discovery algorithm
ICBTA '23: Proceedings of the 2023 6th International Conference on Blockchain Technology and ApplicationsBitcoin’ s anonymity greatly protects users’ privacy, but it also makes regulation difficult. In Bitcoin, a random number generates a public-private key pair, the public key generates an address, and the private key is used for digital signatures. Users ...
On Cancellation of Transactions in Bitcoin-Like Blockchains
On the Move to Meaningful Internet Systems. OTM 2018 ConferencesAbstractBitcoin-like blockchains do not envisage any specific mechanism to avoid unfairness for the users. Hence, unfair situations, like impossibility of cancellation of transactions explicitly or having unconfirmed transactions, reduce the satisfaction ...
Dissecting Bitcoin and Ethereum Transactions: On the Lack of Transaction Contention and Prioritization Transparency in Blockchains
Financial Cryptography and Data SecurityAbstractIn permissionless blockchains, transaction issuers include a fee to incentivize miners to include their transactions. To accurately estimate this prioritization fee for a transaction, transaction issuers (or blockchain participants, mjohnme@mpi-...
Comments
Information & Contributors
Information
Published In
May 2024
4826 pages
ISBN:9798400701719
DOI:10.1145/3589334
- General Chairs:
- Tat-Seng Chua,
- Chong-Wah Ngo,
- Proceedings Chair:
- Roy Ka-Wei Lee,
- Program Chairs:
- Ravi Kumar,
- Hady W. Lauw
Copyright © 2024 ACM.
Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than the author(s) must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected].
Sponsors
Publisher
Association for Computing Machinery
New York, NY, United States
Publication History
Published: 13 May 2024
Check for updates
Author Tags
Qualifiers
- Research-article
Funding Sources
- the National Key R&D Program of China
- STCSM Key Projects
- Natural Science Foundation of China
Conference
WWW '24
Sponsor:
Acceptance Rates
Overall Acceptance Rate 1,899 of 8,196 submissions, 23%
Contributors
Other Metrics
Bibliometrics & Citations
Bibliometrics
Article Metrics
- 0Total Citations
- 89Total Downloads
- Downloads (Last 12 months)89
- Downloads (Last 6 weeks)13
Reflects downloads up to 27 Jul 2024
Other Metrics
Citations
View Options
Get Access
Login options
Check if you have access through your login credentials or your institution to get full access on this article.
Sign in