Catching the Rug: Early Prediction of Fraudulent Memecoins on Solana via Machine Learning
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 mil
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- LinkedLinked via arxiv author · 85%Jianghai Li →
“Catching the Rug: Early Prediction of Fraudulent Memecoins on Solana via Machine Learning”
- LinkedLinked via arxiv author · 85%Pavel Kuznetsov →
“Catching the Rug: Early Prediction of Fraudulent Memecoins on Solana via Machine Learning”
- LinkedLinked via arxiv author · 85%Yury Yanovich →
“Catching the Rug: Early Prediction of Fraudulent Memecoins on Solana via Machine Learning”
- LinkedLinked via arxiv author · 85%Konstantin Nott-Whaley →
“Catching the Rug: Early Prediction of Fraudulent Memecoins on Solana via Machine Learning”
- LinkedLinked via arxiv author · 85%Igor Vodolazov →
“Catching the Rug: Early Prediction of Fraudulent Memecoins on Solana via Machine Learning”
- FuzzySimilar title/name (fuzzy) · 66%stefan-jansen/machine-learning-for-trading →
“Fuzzy title match (0.78): “Catching the Rug: Early Prediction of Fraudulent Memecoins o” ≈ “stefan-jansen/machine-learning-for-trading””