Research on the Optimization and Upgrade of Computer Network Detection Technology in the Intelligent Age

Network security has always been a big problem in the field of computer technology. The purpose of this paper is to optimize and upgrade the computer network detection technology in the intelligent era in modern society, so as to improve the network security defense ability. The network intrusion detection using deep learning is studied through a series of optimization and upgrading schemes. The experimental data show that the accuracy of the test set is improved to 0.990, the recall rate is improved to 0.994, the F1 value is improved to 0.992, and the time consumption is reduced by about 13%. This shows that the proposed optimization and upgrade scheme can effectively improve the accuracy and speed of network detection, thus improving the network security defense capability.