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Code Will Tell: Visual Identification of Ponzi Schemes on Ethereum

Authors :
Wen, Xiaolin
Yeo, Kim Siang
Wang, Yong
Cheng, Ling
Zhu, Feida
Zhu, Min
Publication Year :
2023

Abstract

Ethereum has become a popular blockchain with smart contracts for investors nowadays. Due to the decentralization and anonymity of Ethereum, Ponzi schemes have been easily deployed and caused significant losses to investors. However, there are still no explainable and effective methods to help investors easily identify Ponzi schemes and validate whether a smart contract is actually a Ponzi scheme. To fill the research gap, we propose PonziLens, a novel visualization approach to help investors achieve early identification of Ponzi schemes by investigating the operation codes of smart contracts. Specifically, we conduct symbolic execution of opcode and extract the control flow for investing and rewarding with critical opcode instructions. Then, an intuitive directed-graph based visualization is proposed to display the investing and rewarding flows and the crucial execution paths, enabling easy identification of Ponzi schemes on Ethereum. Two usage scenarios involving both Ponzi and non-Ponzi schemes demonstrate the effectiveness of PonziLens.

Details

Database :
arXiv
Publication Type :
Report
Accession number :
edsarx.2303.07657
Document Type :
Working Paper