A Novel Approach to Predicting Rug-Pull Risks in ERC-20 Smart Contracts

This research proposes two data collection methods, Whole Observation Data (WOD) and 7 Days (7D), for identifying rug-pull risks within ERC-20 smart contracts deployed on the Ethereum blockchain. The WOD method offers a comprehensive, long-term analysis of token activity, while the 7D method focuses on a shorter time frame to detect emerging fraudulent behaviors. Through rigorous experimentation and evaluation, this research demonstrates both methods' reliability, applicability, and predictive capabilities. The findings contribute to a deeper understanding of rug-pull risks and provide valuable insights for developing robust countermeasures to protect in-vestors and maintain the integrity of the cryptocurrency market.

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Publication Details

Published
2024-12-21
DOI
https://doi.org/10.1109/rivf64335.2024.11009094
Primary Topic
Blockchain Technology Applications and Security
Type
article
Field-Weighted Citation Impact
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article

A Novel Approach to Predicting Rug-Pull Risks in ERC-20 Smart Contracts

Cong Nguyen-Thanh, Ngoc Tran-Bao, Trinh Le-Khanh
Blockchain Technology Applications and Security
article

A Novel Approach to Predicting Rug-Pull Risks in ERC-20 Smart Contracts

Cong Nguyen-Thanh, Ngoc Tran-Bao, Trinh Le-Khanh
article en

Abstract

This research proposes two data collection methods, Whole Observation Data (WOD) and 7 Days (7D), for identifying rug-pull risks within ERC-20 smart contracts deployed on the Ethereum blockchain. The WOD method offers a comprehensive, long-term analysis of token activity, while the 7D method focuses on a shorter time frame to detect emerging fraudulent behaviors. Through rigorous experimentation and evaluation, this research demonstrates both methods' reliability, applicability, and predictive capabilities. The findings contribute to a deeper understanding of rug-pull risks and provide valuable insights for developing robust countermeasures to protect in-vestors and maintain the integrity of the cryptocurrency market.

VNU University of Science (VN)
Openalex Percentile: Top 51%
Blockchain Technology Applications and Security
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A Novel Approach to Predicting Rug-Pull Risks in ERC-20 Smart Contracts — Cong Nguyen-Thanh, Ngoc Tran-Bao, et al. · (2024) | TGRS Research Map | TGRS