Network Data Detection for Information Security Using CNN-LSTM Model

Previous researches have mastered rich data resources from big data analysis, built and promoted the network traffic metadata diversion platforms. This paper particularly analyzes the main structure of big data service platforms and big data analysis systems under the network traffic metadata, by using CNN-LSTM machine learning model for data detection. The result accuracy of CNN-LSTM model reaches over 95%, proving that this model can be applied to fulfill the requirements of traffic data sharing and traffic information security.