# High-Frequency Trading on Decentralized On-Chain Exchanges

arXiv: https://arxiv.org/abs/2009.14021 · HTML: https://mlsanity.com/paper/2009.14021/

## Key facts

- Cited by 10 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 29 Sep 2020.

## Built on by (most cited first, 10 of 10)

- [Blockchain Large Language Models](https://mlsanity.com/paper/2304.12749/) (2023)
- [AI Agent Smart Contract Exploit Generation](https://mlsanity.com/paper/2507.05558/) (2025)
- [Ethereum Fraud Detection via Joint Transaction Language Model and Graph Representation Learning](https://mlsanity.com/paper/2409.07494/) (2024)
- [GasTrace: Detecting Sandwich Attack Malicious Accounts in Ethereum](https://mlsanity.com/paper/2405.19971/) (2024)
- [Detecting Various DeFi Price Manipulations with LLM Reasoning](https://mlsanity.com/paper/2502.11521/) (2025)
- [Do not rug on me: Zero-dimensional Scam Detection](https://mlsanity.com/paper/2201.07220/) (2022)
- [LMAE4Eth: Generalizable and Robust Ethereum Fraud Detection by Exploring Transaction Semantics and Masked Graph Embedding](https://mlsanity.com/paper/2509.03939/) (2025)
- [PACE: Policy-Attested Contract Execution for Safe AI Agents in Decentralized Finance](https://mlsanity.com/paper/2608.17220/) (2026)
- [DeFiFusion: Combining Transaction Events with Smart Contracts to Detect Price Manipulation Attacks](https://mlsanity.com/paper/2609.11008/) (2026)
- [EVAGE: Autonomous MEV Generation and Adaptation via Multi-Agent Harness](https://mlsanity.com/paper/2609.27424/) (2026)

## Abstract (arXiv)

Decentralized exchanges (DEXs) allow parties to participate in financial markets while retaining full custody of their funds. However, the transparency of blockchain-based DEX in combination with the latency for transactions to be processed, makes market-manipulation feasible. For instance, adversaries could perform front-running -- the practice of exploiting (typically non-public) information that may change the price of an asset for financial gain. In this work we formalize, analytically exposit and empirically evaluate an augmented variant of front-running: sandwich attacks, which involve front- and back-running victim transactions on a blockchain-based DEX. We quantify the probability of an adversarial trader being able to undertake the attack, based on the relative positioning of a transaction within a blockchain block. We find that a single adversarial trader can earn a daily revenue of over several thousand USD when performing sandwich attacks on one particular DEX -- Uniswap, an exchange with over 5M USD daily trading volume by June 2020. In addition to a single-adversary game, we simulate the outcome of sandwich attacks under multiple competing adversaries, to account for the real-world trading environment.