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Optimal RANDAO Manipulation in Ethereum

Authors Kaya Alpturer , S. Matthew Weinberg

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Author Details

Kaya Alpturer
  • Princeton University, NJ, USA
S. Matthew Weinberg
  • Princeton University, NJ, USA

Funding

Supported by NSF CAREER CCF-1942497 and a grant from the Ripple University Blockchain Research Initiative.

Acknowledgements

We are grateful to Noah Citron for introducing us to the problem, and helpful discussions in early phases of this work. We are also grateful to Yunus Aydın, István Seres, Aadityan Ganesh, and anonymous reviewers for feedback on earlier drafts of this work.

Cite AsGet BibTex

Kaya Alpturer and S. Matthew Weinberg. Optimal RANDAO Manipulation in Ethereum. In 6th Conference on Advances in Financial Technologies (AFT 2024). Leibniz International Proceedings in Informatics (LIPIcs), Volume 316, pp. 10:1-10:21, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2024)
https://doi.org/10.4230/LIPIcs.AFT.2024.10

Abstract

It is well-known that RANDAO manipulation is possible in Ethereum if an adversary controls the proposers assigned to the last slots in an epoch. We provide a methodology to compute, for any fraction α of stake owned by an adversary, the maximum fraction f(α) of rounds that a strategic adversary can propose. We further implement our methodology and compute f(⋅) for all α. For example, we conclude that an optimal strategic participant with 5% of the stake can propose a 5.048% fraction of rounds, 10% of the stake can propose a 10.19% fraction of rounds, and 20% of the stake can propose a 20.68% fraction of rounds.

Subject Classification

ACM Subject Classification
  • Theory of computation → Algorithmic game theory and mechanism design
  • Information systems → Digital cash
  • Security and privacy → Distributed systems security
Keywords
  • Proof of Stake
  • Consensus
  • Blockchain
  • Ethereum
  • Randomness manipulation

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Supplementary Materials

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