Ethereum Phishing Fraud Detection Based on Heterogeneous Transaction Subnets

As one of the most active blockchain platforms at present, Ethereum attracts a great deal of interest, including that of fraudsters. They exploit the anonymity of Ethereum accounts to perpetrate varieties of scams, the most common of which is phishing frauds. However, existing phishing detection work ignores the heterogeneity of Ethereum transaction edges. In fact, the activities on Ethereum include external transactions, internal transactions, and token transactions. Therefore, this paper proposes an Ethereum account phishing fraud detection method named HTSGCN. Based on heterogeneous transaction subnets, our method makes full use of the type and direction information contained in transactions. First, we collect Ethereum transaction data and construct a k-order heterogeneous subnet for each account. To aggregate the neighbor feature, we design a message propagation mechanism based on graph convolution network. Finally, we classify node representation vectors containing neighborhood and its own characteristics. Experimental results show that HTSGCN has a better effect on detecting phishing accounts than previous work which is based on homogeneous networks.