Network Security Situation Awareness Framework based on Knowledge Graph
Jia Chen, Feng Li, Zhenwan Zou, Yingsa Hou · 2023
The mainstream technology of network security protection has gradually transited from the past "rule base" to dynamic perception based on network big data. The development of knowledge atlas has injected new vitality into network security research. Based on the limited Boltzmann machine, this paper realizes the deep learning of network security features, maps them from high dimensional space to low dimensional space layer by layer, and builds a network space security knowledge map. Then, this paper proposes a network security situational awareness framework, which integrates a series of technologies and automation tools, It can automatically and efficiently answer some basic questions that security analysts may put forward in the field of network security situational awareness. At the same time, the attack scenario discovery scheme given by the framework can play a certain role in judging attack behavior in cyberspace and building attack scenarios.