Design of Cross-border Network Crime Detection System Based on PSE and Big Data Analysis

In order to speed up the detection of cybercrime worldwide, a new cross-border cybercrime detection system is designed by introducing the PSE theory and the principle of big data analysis. In the TFTP server, the U-boot network development board and OpenStack crime information detection component are connected to build the hardware running environment of the cross-border network crime detection system. On this basis, through the analysis of the characteristics of detection information, the calculation of cross-border network detection domain and the directional planning of network crime information, the software operating environment of the detection system is built, and the cross-border network crime detection system based on PSE and big data analysis is designed with the basis of hardware implementation. The comparative experimental results show that, compared with the conventional case detection situation, the average detection time of criminal cases is basically maintained between 3-5 days after the application of cross-border cyber crime detection system, and the accuracy of criminal location is maintained at more than 90%.