SADPonzi: Detecting and Characterizing Ponzi Schemes in Ethereum Smart Contracts
Weimin Chen, Xinran Li, Yuting Sui, Ningyu He, Haoyu Wang, Lei Wu, Xiapu Luo
Abstract
Ponzi schemes are financial scams that lure users under the promise of high profits. With the prosperity of Bitcoin and blockchain technologies, there has been growing anecdotal evidence that this classic fraud has emerged in the blockchain ecosystem. Existing studies have proposed machine-learning based approaches for detecting Ponzi schemes. However, these state-of-the-art approaches face several major limitations, including lacking interpretability, high false positive rates and the weak robustness to evasion techniques, These limitations mean that existing real-world methods for detecting Ponzi schemes are ineffective.
Topics & Concepts
InterpretabilityProsperityBlockchainRobustness (evolution)Computer scienceComputer securityArtificial intelligenceEconomicsBiochemistryChemistryGeneEconomic growthBlockchain Technology Applications and SecurityCybercrime and Law Enforcement StudiesCrime, Illicit Activities, and Governance