Honeypot contract detection of blockchain based on deep learning

Abstract

Aiming at the problems of low accuracy of current detection methods and poor generalization of model, a honeypot contract detection method based on KOLSTM deep learning model was proposed.Firstly, by analyzing the characteristics of honeypot contract, the concept of key opcode was proposed, and a keyword extraction method which could be used to select the key opcode in smart contract was designed.Secondly, by adding the key opcode weight mechanism to the traditional LSTM model, a KOLSTM model which could simultaneously capture the sequence features and key opcode features hidden in the honeypot contract was constructed.Finally, the experimental results show that the model had a high recognition accuracy.Compared with the existing methods, the F-score is improved by 2.39% and 19.54% respectively in the two classification and multi-classification detection scenes.

Keywords

• blockchain;Ethereum;smart contract;honeypot contract;deep learning