# Unveiling Wash Trading in Popular NFT Markets

arXiv: https://arxiv.org/abs/2403.10361 · HTML: https://mlsanity.com/paper/2403.10361/

## Key facts

- Cited by 8 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 15 Mar 2024.

## Built on by (most cited first, 8 of 8)

- [SCALM: Detecting Bad Practices in Smart Contracts Through LLMs](https://mlsanity.com/paper/2502.04347/) (2025)
- [AI-Based Vulnerability Analysis of NFT Smart Contracts](https://mlsanity.com/paper/2504.16113/) (2025)
- [A Comprehensive Study of Exploitable Patterns in Smart Contracts: From Vulnerability to Defense](https://mlsanity.com/paper/2504.21480/) (2025)
- [Information Security Based on LLM Approaches: A Review](https://mlsanity.com/paper/2507.18215/) (2025)
- [UEChecker: Detecting Unchecked External Call Vulnerabilities in DApps via Graph Analysis](https://mlsanity.com/paper/2508.01343/) (2025)
- [Agentic AI for Financial Crime Compliance](https://mlsanity.com/paper/2509.13137/) (2025)
- [Resisting Manipulative Bots in Meme Coin Copy Trading: A Multi-Agent Approach with Chain-of-Thought Reasoning](https://mlsanity.com/paper/2601.08641/) (2026)
- [Facial Recognition Leveraging Generative Adversarial Networks](https://mlsanity.com/paper/2505.11884/) (2025)

## Abstract (arXiv)

As emerging digital assets, NFTs are susceptible to anomalous trading behaviors due to the lack of stringent regulatory mechanisms, potentially causing economic losses. In this paper, we conduct the first systematic analysis of four non-fungible tokens (NFT) markets. Specifically, we analyze more than 25 million transactions within these markets, to explore the evolution of wash trade activities. Furthermore, we propose a heuristic algorithm that integrates the network characteristics of transactions with behavioral analysis, to detect wash trading activities in NFT markets. Our findings indicate that NFT markets with incentivized structures exhibit higher proportions of wash trading volume compared to those without incentives. Notably, the LooksRare and X2Y2 markets are detected with wash trading volume proportions as high as 94.5% and 84.2%, respectively.