【Author】
He, Xuezhi; Yang, Tan; Chen, Liping
【Source】SECURITY AND COMMUNICATION NETWORKS
【Abstract】In recent years, blockchain technology has been developing rapidly. More and more traditional industries are using blockchain as a platform for information storage and financial transactions, mainly because of its new characteristics of non-tamperability and decentralization compared with the traditional systems. As a representative of blockchain 2.0, Ethereum has gained popularity upon its introduction. However, because of the anonymity of blockchain, Ethereum has also attracted the attention of some unscrupulous people. Currently, millions of contracts are deployed on Ethereum, many of which are fraudulent contracts deployed by unscrupulous people for profit, and these contracts are causing huge losses to investors worldwide. Ponzi contracts are typical of these contracts, which mainly reward the funds invested by later investors to early investors, and later investors will have no gain. However, although there are some studies for identifying Ponzi contracts on Ethereum, there is some room for progress in the research. Therefore, we propose a method to detect Ponzi scheme contracts on Ethereum-CTRF. This method forms a dataset by extracting the word features and sequence features of the smart contract's code and the features of transactions. The dataset is divided into a training set and a test set. Oversampling is performed on the training set to deal with the problem of positive and negative sample imbalance. Finally, the model is trained on the training set and tested on the test set. The experimental results show that the model has significantly improved recall compared with existing Ponzi contract detection methods.
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