Financial Technology Intelligent Intrusion Detection System based on Financial Data Feature Extraction and DNNs

Financial technology intelligent intrusion detection system based on the financial data feature extraction and DNNs is designed and implemented in this paper. Highlights of the paper are focused on the following aspects. (1) We propose the automatic generation method of the multi-dimensional variation of the test data, and define different data generation rules for different protocol field types by referring to the attack mode of common vulnerabilities. The novel DNNs framework is designed for the analysis of the system. (2) The upgrading of the financial technology in the general terminal interface technology, big data analysis, cloud computing and various data collection methods makes it easier for data, we use the collected data to ensure the further processing framework. The simulation results compared with the state-of-the-art models have proven effectiveness.