SoK: The Evolution of Maximal Extractable Value, From Miners to Cross-Chain
- URL: http://arxiv.org/abs/2603.07716v1
- Date: Sun, 08 Mar 2026 16:37:41 GMT
- Title: SoK: The Evolution of Maximal Extractable Value, From Miners to Cross-Chain
- Abstract summary: We organize the fragmented literature on MEV into a unified chronological framework, beginning with EraI (August 2014 - August 2020)<n>We present a conceptual taxonomy distinguishing potential from realized extractable value, and single-domain from cross-domain phenomena.<n>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.
- Score: 0.0
- License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
- 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.
Related papers
- Quantifying Observable High-Frequency Swapping on Arbitrum [3.2270698896807453]
High-Frequency Swapping (HFS) refers to continuous single-hop swaps at machine cadence within decentralized exchanges.<n>We conduct a large-scale measurement of HFS on Arbitrum, using 18 months of full-chain data.<n>The analysis uncovers 477 distinct HFS swappers responsible for nearly 30 million swaps and over $1011$ USD in notional volume.
arXiv Detail & Related papers (2026-09-13T12:41:03Z) - Towards Decentralized Searcher Competition in MEV Markets [1.4037095606573826]
This paper studies centralization in maximal extractable value markets from the perspective of searcher competition.<n>We develop a heterogeneous model in which searchers differ in opportunity coverage and execution efficiency.<n>We propose an entry-filtered Shapley-capped auction mechanism that distributes searcher rewards more fairly and broadly.
arXiv Detail & Related papers (2026-08-05T16:15:31Z) - Achieving Text-based Person Retrieval with Any Granularity [80.69427598925718]
This paper introduces a new paradigm, Text-based Person Retrieval with Any Granularity.<n>We formalize a five-level granularity spectrum and construct UFine6926-MG, a high-quality multi-grained annotated dataset.<n>We then propose the Cross-modal Multi-grained Aligning and Matching framework.
arXiv Detail & Related papers (2026-07-23T08:42:25Z) - Order Flow Exclusivity and Value Extraction Mechanisms: An Analysis of Ethereum Builder Centralization [10.100078660896108]
This study investigates the rapid centralization of the builder market under the Proposer-Builder Separation (PBS) architecture.<n>We analyze transactions from September 2023 to August 2025 to characterize Exclusive Order Flows (EOFs) and non-atomic Maximal Extractable Value (MEV)<n>A longitudinal analysis of builder strategies delineates the market's evolution into four distinct eras.
arXiv Detail & Related papers (2026-05-06T03:49:23Z) - GoAT-X: A Graph of Auditing Thoughts for Securing Token Transactions in Cross-Chain Contracts [52.51342355102833]
Cross-chain bridges, the critical infrastructure of the multi-chain ecosystem, have become a primary target for attackers.<n>Existing defenses, such as bytecode-level static analysis, are ill-equipped to handle the semantic complexity of cross-chain interactions.<n>We propose GoAT-X, a framework that shifts automated cross-chain smart contracts auditing from pattern matching toward systematic first-principles verification.
arXiv Detail & Related papers (2026-04-27T11:34:21Z) - VLM2GeoVec: Toward Universal Multimodal Embeddings for Remote Sensing [59.73939718087177]
Single-encoder vision-language model trained contrastively to embed interleaved inputs in a unified vector space.<n>VLM2GeoVec unifies scalable retrieval with region-level spatial reasoning, enabling cohesive multimodal analysis in remote sensing.
arXiv Detail & Related papers (2025-12-12T11:39:35Z) - Phase Transition for Stochastic Block Model with more than $\sqrt{n}$ Communities (II) [51.320599504997745]
We show that when the number $K$ of communities remains smaller than $sqrtn$, non-trivial community recovery is possible in time above the Kesten--Stigum threshold.<n>We also show that, in moderately sparse settings, the optimal algorithms appear to be fundamentally different from spectral methods.
arXiv Detail & Related papers (2025-11-26T15:54:17Z) - Certifying optimal MEV strategies with Lean [0.0]
We present the first mechanized formalization of Maximal Extractable Value (MEV)<n>MEV refers to a class of attacks to decentralized applications where the adversary profits by manipulating the ordering, inclusion, or exclusion of transactions in a blockchain.<n>We introduce a methodology to construct machine-checked proofs of MEV bounds, providing correctness guarantees beyond what is possible with existing techniques.
arXiv Detail & Related papers (2025-10-16T09:24:28Z) - METER: Multi-modal Evidence-based Thinking and Explainable Reasoning -- Algorithm and Benchmark [48.78602579128459]
We introduce METER, a unified benchmark for interpretable forgery detection spanning images, videos, audio, and audio-visual content.<n>Our dataset comprises four tracks, each requiring not only real-vs-fake classification but also evidence-chain-based explanations.
arXiv Detail & Related papers (2025-07-22T03:42:51Z) - CoBRA: A Universal Strategyproof Confirmation Protocol for Quorum-based Proof-of-Stake Blockchains [1.5761916307614148]
We present a formal analysis of quorum-based State Machine Replication (SMR) protocols in Proof-of-Stake (PoS) systems under a hybrid threat model comprising honest, Byzantine, and rational validators.<n>Our analysis of traditional quorum-based protocols establishes two fundamental impossibility results: (1) in partially synchronous networks, no quorum-based protocol can achieve SMR when rational and Byzantine validators comprise more than $1/3$ of participants, and (2) in synchronous networks, SMR remains impossible when rational and Byzantine validators comprise $2/3$ or more of participants.
arXiv Detail & Related papers (2025-03-21T01:39:29Z) - Remeasuring the Arbitrage and Sandwich Attacks of Maximal Extractable Value in Ethereum [7.381773144616746]
Maximal Extractable Value (MEV) drives the prosperity of the blockchain ecosystem.
We propose a profitability identification algorithm to identify MEV activities on our collected largest-ever dataset.
We have characterized the overall landscape of the MEV ecosystem, the impact the private transaction architectures bring in, and the adoption of back-running mechanisms.
arXiv Detail & Related papers (2024-05-28T08:17:15Z) - Learning Feature Inversion for Multi-class Anomaly Detection under General-purpose COCO-AD Benchmark [101.23684938489413]
Anomaly detection (AD) is often focused on detecting anomalies for industrial quality inspection and medical lesion examination.
This work first constructs a large-scale and general-purpose COCO-AD dataset by extending COCO to the AD field.
Inspired by the metrics in the segmentation field, we propose several more practical threshold-dependent AD-specific metrics.
arXiv Detail & Related papers (2024-04-16T17:38:26Z) - Hierarchical Audio-Visual Information Fusion with Multi-label Joint
Decoding for MER 2023 [51.95161901441527]
In this paper, we propose a novel framework for recognizing both discrete and dimensional emotions.
Deep features extracted from foundation models are used as robust acoustic and visual representations of raw video.
Our final system achieves state-of-the-art performance and ranks third on the leaderboard on MER-MULTI sub-challenge.
arXiv Detail & Related papers (2023-09-11T03:19:10Z) - VCG Mechanism Design with Unknown Agent Values under Stochastic Bandit
Feedback [104.06766271716774]
We study a multi-round welfare-maximising mechanism design problem in instances where agents do not know their values.
We first define three notions of regret for the welfare, the individual utilities of each agent and that of the mechanism.
Our framework also provides flexibility to control the pricing scheme so as to trade-off between the agent and seller regrets.
arXiv Detail & Related papers (2020-04-19T18:00:58Z)
This list is automatically generated from the titles and abstracts of the papers in this site.
This site does not guarantee the quality of this site (including all information) and is not responsible for any consequences.