Research of network security analysis platform based on big data

Inhalt:
The rapid development of information networks has brought about an explosive growth in the amount of network data that creates challenges to network security. Therefore, it is quickly become a research hotspot in the academic community that using network security situational awareness technology to improve the timeliness and accuracy of network security situation assessment in big data environment. However, the current research does not pay much attention to the construction of the network platform. In this paper, the key technology algorithm of network security situation awareness is optimized by feature extraction based on the combined kernel sparse autoencoder and the network security situation assessment algorithm based on the improved evidence theory. This paper establishes a network security analysis platform based on optimized algorithms and technologies, which provides support for in-depth research on network security.