基于卷积神经网络的网络通信安全态势感知模型

Network Communication Security Situation Awareness Model Based on Convolutional Neural Network

为实现对网络通信安全态势的实时感知,进一步提高对通信节点安全态势感知的精度,本文引进卷积神经网络,设计一种针对网络通信安全态势的感知模型。通过网络通信安全态势数据获取与评价指标设计、基于卷积神经网络的特征数据融合与训练处理、模型安全响应结果输出,完成对感知模型的设计。通过对比实验证明,本文设计的感知模型输出值与期望输出完全一致,安全态势感知的精度较高,可以实现对网络通信安全态势的感知,能够满足研究目的,具有较好的实际应用性能。

In order to realize the real-time awareness of network communication security situation and further improve the accuracy of security situation awareness of communication nodes,convolutional neural network is introduced to design a perception model for network communication security situation.Through the design of network communication security situation data acquisition and evaluation index,the feature data fusion and training processing based on convolutional neural network,and the output of model security response results,the design of perception model is completed.Through comparative experiments,it is proved that the output value of the perception model designed in this paper is completely consistent with the expected output,and the accuracy of security situation awareness is high.It can realize the perception of network communication security situation,meet the research purpose and have good practical application performance.