Journal on Communications ›› 2022, Vol. 43 ›› Issue (1): 194-202.doi: 10.11959/j.issn.1000-436x.2022011

Special Issue: 区块链

• Papers • Previous Articles     Next Articles

Honeypot contract detection of blockchain based on deep learning

Hongxia ZHANG, Qi WANG, Dengyue WANG, Ben WANG   

  1. Qingdao Institute of Software, College of Computer Science and Technology, China University of Petroleum, Qingdao 266580, China
  • Revised:2022-01-05 Online:2022-01-25 Published:2022-01-01
  • Supported by:
    The Major Scientific and Technological Projects of CNPC(ZD2019-183-004);The Fundamental Research Funds for the Central Universities(20CX05019A)

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.

Key words: blockchain, Ethereum, smart contract, honeypot contract, deep learning

CLC Number: 

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