Analyzing and Measuring Censorship and its Effects on the Ethereum Blockchain
Abstract
In August of 2022, the Office of Foreign Assets Control (OFAC) imposed sanctions on Tornado Cash, a privacy service on the Ethereum blockchain network. The consequences of this decision resulted in many centralized service providers refraining from accepting transactions to Tornado Cash. This negatively impacted the user experience of those who intended to utilize the privacy service significantly. The occurrence raises questions regarding the level of censorship resistance that Ethereum possesses. Censorship resistance is a crucial requirement for credible neutrality, which is a fundamental value that Ethereum must uphold to remain a permissionless and public network. This thesis aims to investigate censorship and centralization on the Ethereum network, specifically the extent and effectiveness of censorship, as well as assess the efficacy of proposed solutions to counteract censorship. The research will also examine the influence that Maximal Extractable Value (MEV) has on censorship and centralization in the current Ethereum block building market and evaluate, whether there is an significant profit difference between non-censoring and censoring actors in the network.
Research Questions
- How much censorship occurs on Ethereum and does MEV influence it?
1.1 Investigate techniques for identifying censorship on the Ethereum network
1.2 Should we include all forms of censorship, such as blacklisted addresses by centralized stablecoins?
1.3 Establish the requirements neeeded for monitoring censorship on the Ethereum platform.
1.4 Explore whether MEV has an impact on censorship and how to measure it.
- How effective is censorship on Ethereum?
2.1 Think of possible metrics to measure effectiveness of censorship.
2.2 Investigate techniques for quantifying transactions using the identified metrics.
2.3 Identify the necessary prerequisites to accomplish the aforementioned tasks.
- What is the profit difference between non-censoring and censoring network participants on Ethereum, and does this vary based on whether they have joined specialized MEV marketplaces?
3.1 Research how to identify censoring and non-censoring network participants not running MEV-Boost
3.2 Research how to identify censoring and non-censoring network participants running MEV-Boost
3.3 Research methods to quantify the profit difference.
3.4 Identify the necessary prerequisites to accomplish the aforementioned tasks.
- Can censorship be mitigated?
4.1 Explore methods for detecting if a transaction is undergoing censorship or not
4.2 Research censorship mitigation measures
4.3 Determine the feasibility of implementing these measures for empirical evaluation
References
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Daian et al., 2019 Flash Boys 2.0: Frontrunning, Transaction Reordering, and Consensus Instability in Decentralized Exchanges
- thegostep, 2021 MEV-Boost: Merge ready Flashbots Architecture
- Hasu, 2022 Understanding MEV-Boost Liveness Risks
- Brown, 2022 MEV-Driven Centralization in Ethereum Part 2
- Monnot, 2022 Notes on Proposer Builder Separation
- Buterin, 2022 State of Research: Increasing Censorship Resistance of transactions under Proposer/Builder Separation (PBS)
- Wahrstätter, 2023 Builders on MEV - Analysing the impact of the OFAC sanctions on Block Builders.
- Buterin, 2021 Proposer/block builder separation-friendly fee market designs
- Monnot, 2022 Unbundling PBS: Towards protocol enforced proposer commitments
- Flashbots, 2022 The future is SUAVE
- Ambergroup, 20222 Extractable Value