Statistical Confidence in Mining Power Estimates for PoW Blockchains
Pages 1752 - 1760
Abstract
The security of blockchain systems depends on the distribution of mining power across participants. If sufficient mining power is controlled by one entity, they can force their own version of events. This may allow them to double spend coins, for example. For Proof of Work (PoW) blockchains, however, the distribution of mining power cannot be read directly from the blockchain and must instead be inferred from the number of blocks mined in a specific sample window. We introduce a framework to quantify this statistical uncertainty for the Nakamoto coefficient, which is a commonly-used measure of blockchain decentralization. We show that aggregating blocks over a day can lead to considerable uncertainty, with Bitcoin failing more than half the hypothesis tests (α=0.05) when using a daily granularity. For these reasons, we recommend that blocks are aggregated over a sample window of at least 7 days. Instead of reporting a single value, our approach produces a range of possible Nakamoto coefficient values that have statistical support at a particular significance level α.
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References
[1]
Alireza Beikverdi and JooSeok Song. 2015. Trend of centralization in Bitcoin's distributed network. In 2015 IEEE/ACIS 16th international conference on software engineering, artificial intelligence, networking and parallel/distributed computing (SNPD). IEEE, IEEE Computer Society, 1730 Massachusetts Avenue N.W., Washington, D.C., USA, 1--6.
[2]
David Jean Biau, Brigitte M Jolles, and Raphaël Porcher. 2010. P value and the theory of hypothesis testing: an explanation for new researchers. Clinical Orthopaedics and Related Research®, Vol. 468, 3 (2010), 885--892.
[3]
Blockchain.com. 2024. Hashrate Distribution: An estimation of hashrate distribution amongst the largest mining pools. https://www.blockchain.com/explorer/charts/pools
[4]
Carlo Campajola, Raffaele Cristodaro, Francesco Maria De Collibus, Tao Yan, Nicolo' Vallarano, and Claudio J. Tessone. 2023. The Evolution Of Centralisation on Cryptocurrency Platforms. arxiv: 2206.05081 [physics.soc-ph]
[5]
Sérgio Fernandes and Jorge Bernardino. 2015. What is BigQuery?. In Proceedings of the 19th International Database Engineering & Applications Symposium (Yokohama, Japan) (IDEAS '15). Association for Computing Machinery, New York, NY, USA, 202--203. https://doi.org/10.1145/2790755.2790797
[6]
Robin Fritsch, Marino Müller, and Roger Wattenhofer. 2022. Analyzing Voting Power in Decentralized Governance: Who controls DAOs?arxiv: 2204.01176 [cs.CY]
[7]
Juan Garay, Aggelos Kiayias, and Nikos Leonardos. 2015. The Bitcoin Backbone Protocol: Analysis and Applications. In Advances in Cryptology - EUROCRYPT 2015, Elisabeth Oswald and Marc Fischlin (Eds.). Springer Berlin Heidelberg, Berlin, Heidelberg, 281--310.
[8]
Dominic Grandjean, Lioba Heimbach, and Roger Wattenhofer. 2023. Ethereum Proof-of-Stake Consensus Layer: Participation and Decentralization. arxiv: 2306.10777 [cs.DC]
[9]
John PA Ioannidis. 2005. Why most published research findings are false. PLoS medicine, Vol. 2, 8 (2005), e124.
[10]
Johannes Rude Jensen, Victor von Wachter, and Omri Ross. 2021. How Decentralized is the Governance of Blockchain-based Finance: Empirical Evidence from four Governance Token Distributions. arxiv: 2102.10096 [q-fin.GN]
[11]
Bartosz Kusmierz and Roman Overko. 2022. How centralized is decentralized? Comparison of wealth distribution in coins and tokens. In 2022 IEEE International Conference on Omni-layer Intelligent Systems (COINS). IEEE Computer Society, 1730 Massachusetts Avenue N.W., Washington, D.C., USA, 1--6. https://doi.org/10.1109/COINS54846.2022.9854972
[12]
Chao Li, Balaji Palanisamy, Runhua Xu, and Li Duan. 2023. Cross-Consensus Measurement of Individual-level Decentralization in Blockchains. In 2023 IEEE 9th Intl Conference on Big Data Security on Cloud (BigDataSecurity), IEEE Intl Conference on High Performance and Smart Computing, (HPSC) and IEEE Intl Conference on Intelligent Data and Security (IDS). IEEE Computer Society, 1730 Massachusetts Avenue N.W., Washington, D.C., USA, 45--50. https://doi.org/10.1109/BigDataSecurity-HPSC-IDS58521.2023.00018
[13]
Jian-Hong Lin, Emiliano Marchese, Claudio J. Tessone, and Tiziano Squartini. 2022. The weighted Bitcoin Lightning Network. Chaos, Solitons & Fractals, Vol. 164 (2022), 112620. https://doi.org/10.1016/j.chaos.2022.112620
[14]
Qinwei Lin, Chao Li, Xifeng Zhao, and Xianhai Chen. 2021. Measuring Decentralization in Bitcoin and Ethereum using Multiple Metrics and Granularities. In 2021 IEEE 37th International Conference on Data Engineering Workshops (ICDEW). IEEE Computer Society, 1730 Massachusetts Avenue N.W., Washington, D.C., USA, 80--87. https://doi.org/10.1109/ICDEW53142.2021.00022
[15]
Jingyu Liu, Lu Liu, Zijing Li, and Chao Li. 2023. DeMonitor: Monitoring Decentralization in Blockchains using BigQuery. In 2023 IEEE International Conference on Blockchain and Cryptocurrency (ICBC). IEEE Computer Society, 1730 Massachusetts Avenue N.W., Washington, D.C., USA, 1--2. https://doi.org/10.1109/ICBC56567.2023.10174900
[16]
Arvind Narayanan, Joseph Bonneau, Edward Felten, Andrew Miller, and Steven Goldfeder. 2016. Bitcoin and cryptocurrency technologies: a comprehensive introduction. Princeton University Press, 41 William Street, Princeton, NJ, USA.
[17]
Christina Ovezik, Dimitris Karakostas, and Aggelos Kiayias. 2024. SoK: A Stratified Approach to Blockchain Decentralization. In International Conference on Financial Cryptography and Data Security. Springer, International Financial Cryptography Association, Amsterdam, NL.
[18]
Matteo Romiti, Aljosha Judmayer, Alexei Zamyatin, and Bernhard Haslhofer. 2019. A Deep Dive into Bitcoin Mining Pools: An Empirical Analysis of Mining Shares. arxiv: 1905.05999 [cs.CR]
[19]
Balaji S. Srinivasan and Leland Lee. 2017. Quantifying Decentralization. Medium. https://news.earn.com/quantifying-decentralization-e39db233c28e Retrieved March 11, 2024 from
[20]
Eileen Tipoe and Ralf Becker. 2020. Measuring Inequality: Lorenz Curves and Gini Coefficients. Electric Book Works, Cape Town, South Africa. https://www.core-econ.org/doing-economics/book/text/05-02.html(visited 2024-03--11).
[21]
Liyi Zeng, Yang Chen, Shuo Chen, Xian Zhang, Zhongxin Guo, Wei Xu, and Thomas Moscibroda. 2021. Characterizing Ethereum's Mining Power Decentralization at a Deeper Level. In IEEE INFOCOM 2021 - IEEE Conference on Computer Communications. IEEE Computer Society, 1730 Massachusetts Avenue N.W., Washington, D.C., USA, 1--10. https://doi.org/10.1109/INFOCOM42981.2021.9488812
[22]
Rui Zhang, Rui Xue, and Ling Liu. 2019. Security and privacy on blockchain. ACM Computing Surveys (CSUR), Vol. 52, 3 (2019), 1--34. io
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Published In
May 2024
1928 pages
ISBN:9798400701726
DOI:10.1145/3589335
- General Chairs:
- Tat-Seng Chua,
- Chong-Wah Ngo,
- Program Chairs:
- Ravi Kumar,
- Hady W. Lauw,
- Roy Ka-Wei Lee
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This work is licensed under a Creative Commons Attribution International 4.0 License.
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Published: 13 May 2024
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