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Maximal Extractable Value Mitigation Approaches in Ethereum and Layer-2 Chains: A Comprehensive Survey (2407.19572v1)

Published 28 Jul 2024 in cs.CR

Abstract: Maximal Extractable Value (MEV) represents a pivotal challenge within the Ethereum ecosystem; it impacts the fairness, security, and efficiency of both Layer 1 (L1) and Layer 2 (L2) networks. MEV arises when miners or validators manipulate transaction ordering to extract additional value, often at the expense of other network participants. This not only affects user experience by introducing unpredictability and potential financial losses but also threatens the underlying principles of decentralization and trust. Given the growing complexity of blockchain applications, particularly with the increase of Decentralized Finance (DeFi) protocols, addressing MEV is crucial. This paper presents a comprehensive survey of MEV mitigation techniques as applied to both Ethereums L1 and various L2 solutions. We provide a novel categorization of mitigation strategies; we also describe the challenges, ranging from transaction sequencing and cryptographic methods to reconfiguring decentralized applications (DApps) to reduce front-running opportunities. We investigate their effectiveness, implementation challenges, and impact on network performance. By synthesizing current research, real-world applications, and emerging trends, this paper aims to provide a detailed roadmap for researchers, developers, and policymakers to understand and combat MEV in an evolving blockchain landscape.

Citations (1)

Summary

  • The paper systematically categorizes MEV mitigation methods in Ethereum and L2 chains, emphasizing fair ordering and privacy-preserving techniques.
  • It evaluates approaches ranging from FCFS and decentralized sequencing to threshold and delay encryption to counteract transaction manipulation.
  • The survey highlights innovative PBS and shared sequencing solutions as key avenues for future research to enhance blockchain fairness and security.

Maximal Extractable Value Mitigation Approaches in Ethereum and Layer-2 Chains: A Comprehensive Survey

The paper “Maximal Extractable Value Mitigation Approaches in Ethereum and Layer-2 Chains: A Comprehensive Survey” authored by Zeinab Alipanahloo, Abdelhakim Senhaji Hafid, and Kaiwen Zhang, explores the intricacies of Maximal Extractable Value (MEV) and various strategies designed to mitigate its impact on Ethereum and Layer-2 chains. This survey is an essential read for researchers and practitioners of blockchain technology, offering in-depth analysis and categorization of MEV mitigation techniques.

MEV represents the profit miners or validators can make by manipulating the order of transactions within a block, often at the expense of regular network participants. This practice distorts transaction fairness, challenges decentralization principles, and introduces security vulnerabilities. As the ecosystem of Decentralized Finance (DeFi) expands, understanding and combating MEV becomes increasingly critical.

Overview of MEV Mitigation Strategies

The paper organizes MEV mitigation techniques into two primary strategies: prevention/reduction and side-effect reduction.

Fair Ordering Policies

These policies are implemented to ensure transactions are orderly processed in a way that minimizes MEV opportunities. Techniques range from simple First-Come-First-Serve (FCFS) algorithms to more complex decentralized sequencing methods.

  • Single Sequencer Approaches: The FCFS ordering policy is typical, exemplified by protocols like Arbitrum and Optimism. However, this method can lead to issues such as latency wars and spam attacks.
  • Decentralized Sequencing: This involves multiple nodes agreeing on transaction orders to avoid single points of failure. Protocols like Themis and Wendy exemplify advanced decentralized transaction ordering without requiring synchronized clocks, thereby enhancing fairness and security.
  • Shared Sequencers: This burgeoning concept aims to provide sequencing across multiple Rollups to reduce operational costs and resource fragmentation. Espresso is a notable example implementing a decentralized shared sequencer network.

Privacy-Preserving Methods

These methods focus on hiding transaction details until their place in the block is confirmed, effectively preventing front-running.

  • Threshold Encryption: Involves splitting the decryption key among multiple key holders, requiring a majority to decrypt transactions, thus distributing trust.
  • Delay Encryption: Utilizes time-lock puzzles to keep transactions encrypted for a set period, ensuring that no early decryption can take place.
  • TEEs: Transactions are encrypted and held within secure hardware environments, decrypted only after final ordering, providing robust privacy assurances but introducing hardware dependencies.

Smart Contract-Level Protection

Targeted at the application layer, this method redesigns smart contracts to inherently reduce MEV risks. CoWswap and FairMM highlight the blend of off-chain and on-chain mechanisms to secure trades against front-running and other attacks.

Proposer-Builder Separation (PBS)

This approach disaggregates the roles of block proposers and builders to democratize the MEV extraction process. MEV-Boost is a current implementation, leveraging a decentralized network of block builders to enhance diversity and fairness among blockchain participants.

Implications and Future Research

The survey's detailed examination of these techniques showcases the unique strengths and weaknesses of each approach. For instance, while fair ordering policies can mitigate many forms of MEV, they also require intricate coordination and trust in sequencers. Privacy-preserving methods, particularly delay encryption, shine due to their trustless nature but come with computational overhead.

PBS, as implemented in MEV-Boost, demonstrates a significant shift toward equitable MEV benefits distribution but requires more work to mitigate centralization risks posed by relay nodes.

The promising avenue of shared sequencing and advancements in cryptographic primitives like witness encryption present opportunities for future research and development. These innovations could further enhance fairness, security, and efficiency in mitigating MEV, fostering a more robust and trustworthy blockchain ecosystem.

In essence, the paper contributes substantially to the blockchain research community by systematically analyzing and categorizing MEV mitigation techniques. It points the way forward for future developments, emphasizing the continuous need for innovation to address evolving challenges in blockchain technology.

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