SoK: The Evolution of Maximal Extractable Value, From Miners to Cross-Chain

TL;DR

This paper systematically analyzes the historical development of Maximal Extractable Value (MEV) in blockchain, from early miner-based systems to modern cross-chain ecosystems, highlighting key concepts, mitigations, and future research directions.

Contribution

It provides a comprehensive, unified framework organizing MEV research into three eras, introduces a taxonomy distinguishing potential and realized, single-domain and cross-domain MEV, and outlines future research challenges.

Findings

Identified three distinct eras of MEV evolution.

Proposed a taxonomy differentiating potential vs. realized and single-domain vs. cross-chain MEV.

Highlighted measurement challenges and proposed a research agenda.

Abstract

This Systematization of Knowledge (SoK) provides a comprehensive historical analysis of Maximal Extractable Value (MEV) in blockchain systems, tracing its conceptual evolution through three distinct eras. We organize the fragmented literature on MEV into a unified chronological framework, beginning with Era~I (August 2014 - August 2020), which introduced Miner Extractable Value from pmcgoohan's seminal Reddit warning through the ``Dark Forest'' recognition, covering Proof-of-Work systems with public mempools and Priority Gas Auctions. Era~II (August 2020 - April 2024) marks the generalization to Maximal Extractable Value, encompassing formal taxonomies, Realized Extractable Value, Proposer-Builder Separation, the Ethereum Merge, MEV-Boost, and the integration of non-atomic and CEX-DEX arbitrage. Era~III (April 2024, present) addresses the frontier of Cross-Chain MEV, beginning with early studies on Layer-2 ecosystems, where value extraction spans multiple blockchains, rollups, bridges, and sequencers. We present a conceptual taxonomy distinguishing potential from realized extractable value, and single-domain from cross-domain phenomena. Our systematization identifies mitigations that emerged in response to each era, highlights measurement challenges, and proposes a research agenda for standardized metrics, detection benchmarks, and cross-chain infrastructure design.