# Unraveling the MEV Enigma: ABI-Free Detection Model using Graph Neural Networks

arXiv: https://arxiv.org/abs/2305.05952 · HTML: https://mlsanity.com/paper/2305.05952/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 10 May 2023.

## Built on by (most cited first, 1 of 1)

- [If It Walks Like an Arbitrage: Protocol-Agnostic Detection with Decidable Structural Equivalence](https://mlsanity.com/paper/2608.20377/) (2026)

## Abstract (arXiv)

The detection of Maximal Extractable Value (MEV) in blockchain is crucial for enhancing blockchain security, as it enables the evaluation of potential consensus layer risks, the effectiveness of anti-centralization solutions, and the assessment of user exploitation. However, existing MEV detection methods face limitations due to their low recall rate, reliance on pre-registered Application Binary Interfaces (ABIs) and the need for continuous monitoring of new DeFi services. In this paper, we propose ArbiNet, a novel GNN-based detection model that offers a low-overhead and accurate solution for MEV detection without requiring knowledge of smart contract code or ABIs. We collected an extensive MEV dataset, surpassing currently available public datasets, to train ArbiNet. Our implemented model and open dataset enhance the understanding of the MEV landscape, serving as a foundation for MEV quantification and improved blockchain security.