中圖分類號： TN03；TP393.0 文獻標識碼： A DOI：10.16157/j.issn.0258-7998.200900 中文引用格式： 熊中浩，張偉，楊國玉. 基于DBN的網(wǎng)絡安全態(tài)勢評估和態(tài)勢預測建模研究[J].電子技術應用，2021，47(5)：35-39，44. 英文引用格式： Xiong Zhonghao，Zhang Wei，Yang Guoyu. Research on network security situation assessment and situation prediction modeling based on DBN[J]. Application of Electronic Technique，2021，47(5)：35-39，44.
Research on network security situation assessment and situation prediction modeling based on DBN
Xiong Zhonghao1，2，Zhang Wei1，Yang Guoyu1
1.China Datang Corporation Science and Technology Research Institute，Beijing 100040，China； 2.Datang Hydropower Research Institute Co.，Ltd.，Chengdu 610031，China
Abstract： With the rapid development and rapid development of computer communication network technology, network attacks and destruction emerge in various forms and emerge in endlessly. Situation awareness system provides a comprehensive guarantee for network security. Improving the stability, accuracy and rapidity of situation assessment and situation prediction modeling is an important direction of situation awareness system research. As a deep learning intelligent algorithm, deep belief network brings new direction to the accuracy and theorization of network security situation assessment and situation prediction. Considering the deep belief network algorithm, the restricted Boltzmann machine is used as the basic network, and layer by layer pre-training and fine tuning are the core parts of the network. The generalized network security situation assessment index system is constructed, and the data-driven model of situation assessment and situation prediction of computer communication network security is established. Experimental simulation is carried out through the intrusion detection data set CIC-IDS2017 to verify the accuracy and effectiveness of the model.
Key words : network security；situation assessment；situation prediction；deep belief network；modeling and simulation
