基于NH-DBNs的网络空间态势预测

结合网络空间态势研判的实际问题, 对网络态势变量预测进行研究, 提出基于NH-DBNs模型的网络态势预测方法, 以解决现有模型单时序回归和忽略多变量之间相互影响的问题。给出了网络态势的呈现方式和态势预测的方法与流程。在同一个环境下进行对比实验, 证明该算法符合实际应用环境, 且能够提升网络空间态势指标预测的精确性, 对辅助指挥者科学、合理、精确决策具有一定参考价值。

Abstract

To address the practical problems in the prediction and assessment of cyberspace state, this paper studies the prediction of variables in cyberspace, and presents a state prediction method based on Non-Homogeneous Dynamic Bayesian Networks (NH-DBNs), so as to solve the problems in the existing model of single time-sequence regression and the ignorance of the inter-influence between multiple variables.The presenting form of the network state is given, and the method and process of state prediction are presented. The comparison experiment conducted in the same environment has proved that the algorithm accords with the practical application environment, and can improve the prediction accuracy of the indexes of the cyberspace state. The algorithm has certain value for the conductor to make scientific, reasonable and accurate decisions.

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王劲松, 吴天昊, 朱兴奎, 颜文琦. 基于NH-DBNs的网络空间态势预测[J]. 电光与控制, 2019, 26(2): 44. WANG Jinsong, WU Tianhao, ZHU Xingkui, YAN Wenqi. NH-DBNs Based Cyberspace State Prediction[J]. Electronics Optics & Control, 2019, 26(2): 44.

基于NH-DBNs的网络空间态势预测

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