PonziGuard: Detecting Ponzi Schemes on Ethereum with Contract Runtime Behavior Graph (CRBG)
Ruichao Liang, Jing Chen, Kun He, Yueming Wu, Gelei Deng, Ruiying Du, Cong Wu
Abstract
Ponzi schemes, a form of scam, have been discovered in Ethereum smart contracts in recent years, causing massive financial losses. Rule-based detection approaches rely on pre-defined rules with limited capabilities and domain knowledge dependency. Additionally, using static information like opcodes and transactions for machine learning models fails to effectively characterize the Ponzi contracts, resulting in poor reliability and interpretability.
Topics & Concepts
InterpretabilityOpcodeComputer scienceDependency (UML)Smart contractDependency graphDomain (mathematical analysis)GraphReliability (semiconductor)Computer securityTheoretical computer scienceMachine learningArtificial intelligenceBlockchainOperating systemMathematicsMathematical analysisPhysicsQuantum mechanicsPower (physics)Blockchain Technology Applications and SecuritySpam and Phishing DetectionCrime, Illicit Activities, and Governance