Detecting Phishing Scams on Ethereum Based on Transaction Records

With the increasing popularity of blockchain technology, it has also become a hotbed of various cybercrimes. As a traditional way of scam, the phishing scam has new means of scam in the blockchain scenario and swindles a lot of money from users. In order to create a safe environment for investors, an efficient method for phishing detection is urgently needed. In this paper, we propose a three steps framework to detect phishing scams on Ethereum by mining Ethereum transaction records. First, we obtain the labeled phishing accounts and corresponding transaction records from two authorized websites. According to the collected transaction records we build an Ethereum transaction network. Then, a network embedding method node2vec which can extract the latent features of accounts is used for subsequent phishing classification. Finally, to distinguish whether the account is a phishing account, we adopt the one-class support vector machine (SVM) to classify. The experimental result demonstrates that F-score of our phishing detection method can achieve 0.846, which verifies the validity of our model. To the best of our knowledge, this is the first work that investigates the phishing scams on Ethereum based on transaction records.