发表机构
Higher School of Economics; Moscow State University; Skolkovo Institute of Science and Technology（高等经济学院; 莫斯科国立大学; 斯科尔科沃科学技术研究院）
机构由 AI 辅助整理，请以论文原文为准。AI 中文总结
本研究针对Solana平台模因币的“ rug pull”欺诈问题，利用XGBoost等经典机器学习模型，基于交易初期5分钟数据实现早期检测，多源数据融合提升了跨平台泛化能力，为投资者提供了保护框架。
AI 中文摘要
区块链平台上模因币的快速增殖增加了欺诈活动的风险，尤其是“ rug pull”（ rug pull指项目方卷走投资者资金的欺诈行为）。以往研究多聚焦于以太坊上的代币，而本文将研究重点转向Solana——这个以交易量和代币数量计领先的模因币区块链。与以太坊上“ rug pull”常利用智能合约后门不同，Solana模因币的“ rug pull”主要由流动性操纵和社交动态驱动。本研究开创性地在Solana生态系统中开展大规模“ rug pull”早期检测，收集了7个月内640万个代币的数据集。市场分析显示，绝大多数这类模因币在上线后1小时内就呈现出“ rug pull”特征，凸显了短时间窗预测的紧迫性。尽管缺乏代码层面的特征，我们证明经典机器学习模型，尤其是梯度提升模型（XGBoost），仅利用交易最初5分钟的数据就能实现对潜在“ rug pull”的稳健检测。此外，我们评估了PumpFun和Raydium之间的跨平台泛化能力，发现多源数据融合可显著缓解领域偏移，提升检测可靠性。本研究加深了对高吞吐量链上DeFi欺诈的理解，为保护投资者提供了实用框架。
英文摘要
The rapid proliferation of memecoins on blockchain platforms has increased the risk of fraudulent activities, particularly rug pulls. While previous studies have focused on Ethereum-based tokens, this paper shifts the spotlight to Solana, the leading blockchain for memecoins by trading volume and token count. Unlike Ethereum, where rug pulls often exploit smart contract backdoors, Solana memecoin rug pulls are predominantly driven by liquidity manipulation and social dynamics. This research pioneers large-scale rug pull early detection in the Solana ecosystem by assembling a dataset of 6.4 million tokens over 7 months. Market analysis reveals that a vast majority of these memecoins exhibit rug pull characteristics within one hour of launch, highlighting the urgency of short-horizon prediction. Despite the absence of code-level features, we demonstrate that classic machine learning models, particularly Gradient Boosting (XGBoost), achieve robust performance in detecting potential rug pulls using only the first 5 minutes of trading data. Furthermore, we evaluate cross-platform generalization between PumpFun and Raydium, revealing that multi-source data fusion significantly mitigates domain shift and improves detection reliability. This study advances the understanding of DeFi fraud on high-throughput chains and provides a practical framework for protecting investors.
