Statistical Confidence in Mining Power Estimates for PoW Blockchains

Fuente: arXiv
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Auteurs principaux: Milad, Mary, Ovezik, Christina, Karakostas, Dimitris, Woods, Daniel W.
Format: Preprint
Publié: 2024
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author Milad, Mary
Ovezik, Christina
Karakostas, Dimitris
Woods, Daniel W.
author_facet Milad, Mary
Ovezik, Christina
Karakostas, Dimitris
Woods, Daniel W.
contents 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.
format Preprint
id arxiv_https___arxiv_org_abs_2403_13736
institution arXiv
publishDate 2024
record_format arxiv
spellingShingle Statistical Confidence in Mining Power Estimates for PoW Blockchains
Milad, Mary
Ovezik, Christina
Karakostas, Dimitris
Woods, Daniel W.
Cryptography and Security
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.
title Statistical Confidence in Mining Power Estimates for PoW Blockchains
topic Cryptography and Security
url https://arxiv.org/abs/2403.13736