Paper mainly focuses on the Ponzi scheme, atypical fraud, which has caused large property damage to the users in Ethereum . It proposes a detecting model based on graph convolutionalnetwork (GCN) to precisely distinguishPonzi contracts . Experiments on differentreal-world . datasets demonstrate that our proposed model has promising results compared with . general machine learning methods to detect Ponzisi schemes . The paper mainly focuses . on the . proposed model of detecting model has . promising results . Compared with general machine . learning methods, the proposed model is promising compared with general . machine learning method to detect . Ponzimsi contracts to maintain Ethereum’s sustainable development, we propose a . model . We first collect target contracts’ transactions to establish transactions to . establishtransaction networks and propose a new model

Author(s) : Shanqing Yu, Jie Jin, Yunyi Xie, Jie Shen, Qi Xuan

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Keywords : model - machine - learning - general - compared -

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