Honeypot contract detection of blockchain based on deep learning
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 ke...
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| Main Authors: | , , , |
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| Format: | Article |
| Language: | zho |
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Editorial Department of Journal on Communications
2022-01-01
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| Series: | Tongxin xuebao |
| Subjects: | |
| Online Access: | http://www.joconline.com.cn/zh/article/doi/10.11959/j.issn.1000-436x.2022011/ |
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| _version_ | 1841539935108071424 |
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| author | Hongxia ZHANG Qi WANG Dengyue WANG Ben WANG |
| author_facet | Hongxia ZHANG Qi WANG Dengyue WANG Ben WANG |
| author_sort | Hongxia ZHANG |
| collection | DOAJ |
| description | 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. |
| format | Article |
| id | doaj-art-29e1dcbfb3cd4e2184821aabbab96406 |
| institution | Kabale University |
| issn | 1000-436X |
| language | zho |
| publishDate | 2022-01-01 |
| publisher | Editorial Department of Journal on Communications |
| record_format | Article |
| series | Tongxin xuebao |
| spelling | doaj-art-29e1dcbfb3cd4e2184821aabbab964062025-01-14T06:30:32ZzhoEditorial Department of Journal on CommunicationsTongxin xuebao1000-436X2022-01-014319420259398645Honeypot contract detection of blockchain based on deep learningHongxia ZHANGQi WANGDengyue WANGBen WANGAiming 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.http://www.joconline.com.cn/zh/article/doi/10.11959/j.issn.1000-436x.2022011/blockchainEthereumsmart contracthoneypot contractdeep learning |
| spellingShingle | Hongxia ZHANG Qi WANG Dengyue WANG Ben WANG Honeypot contract detection of blockchain based on deep learning Tongxin xuebao blockchain Ethereum smart contract honeypot contract deep learning |
| title | Honeypot contract detection of blockchain based on deep learning |
| title_full | Honeypot contract detection of blockchain based on deep learning |
| title_fullStr | Honeypot contract detection of blockchain based on deep learning |
| title_full_unstemmed | Honeypot contract detection of blockchain based on deep learning |
| title_short | Honeypot contract detection of blockchain based on deep learning |
| title_sort | honeypot contract detection of blockchain based on deep learning |
| topic | blockchain Ethereum smart contract honeypot contract deep learning |
| url | http://www.joconline.com.cn/zh/article/doi/10.11959/j.issn.1000-436x.2022011/ |
| work_keys_str_mv | AT hongxiazhang honeypotcontractdetectionofblockchainbasedondeeplearning AT qiwang honeypotcontractdetectionofblockchainbasedondeeplearning AT dengyuewang honeypotcontractdetectionofblockchainbasedondeeplearning AT benwang honeypotcontractdetectionofblockchainbasedondeeplearning |