首页|Monitoring and Early Warning of New Cyber-Telecom Crime Platform Based on BERT Migration Learning
Monitoring and Early Warning of New Cyber-Telecom Crime Platform Based on BERT Migration Learning
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NETL
NSTL
万方数据
维普
The network is a major platform for implementing new cyber-telecom crimes. Therefore, it is important to carry out mon-itoring and early warning research on new cyber-telecom crime platforms, which will lay the foundation for the establishment of prevention and control systems to protect cit-izens' property. However, the deep-learning methods applied in the monitoring and early warning of new cyber-telecom crime plat-forms have some apparent drawbacks. For instance, the methods suffer from data-dis-tribution differences and tremendous manual efforts spent on data labeling. Therefore, a monitoring and early warning method for new cyber-telecom crime platforms based on the BERT migration learning model is proposed. This method first identifies the text data and their tags, and then performs migration train-ing based on a pre-training model. Finally, the method uses the fine-tuned model to predict and classify new cyber-telecom crimes. Exper-imental analysis on the crime data collected by public security organizations shows that higher classification accuracy can be achieved using the proposed method, compared with the deep-learning method.
new cyber-telecom crimeBERT modeldeep learningmonitoring and warn-ingtext analysis
Shengli Zhou、Xin Wang、Zerui Yang
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Information Department of Zhejiang Police College, Hangzhou 310053, China
International School of Zhejiang Police College, Hangzhou 310053, China
This work was supported in part by the Basic Public Welfare Research Program of Zhejiang Province
NETL
NSTL
万方数据
维普
