基于深度学习的校园网络安全风险评估与预测分析  

Analysis of Campus Network Security Risk Assessment and Prediction Analysis Based on Deep Learning

作　　者：文静 WEN Jing(Hubei University of Commerce and Trade,Hubei 430079,China)

机构地区：[1]湖北商贸学院,湖北430079

出　　处：《电子技术（上海）》2024年第9期410-412,共3页Electronic Technology

摘　　要：阐述一种基于深度学习的校园网络安全风险评估与预测方法。构建一个多维度网络安全风险评估指标体系,包括网络设备、应用系统、数据资产方面安全指标。设计基于长短期记忆神经网络(LSTM)的深度学习模型,用于建模网络安全风险的时序特征,实现风险预测,实验验证方法的有效性。This paper expounds a campus network security risk assessment and prediction method based on deep learning. It constructs a multidimensional network security risk assessment index system, including security indicators for network devices, application systems, and data assets. It designs a deep learning model based on Long Short Term Memory(LSTM) neural network to model the temporal characteristics of network security risks, achieve risk prediction, and experimentally verify the effectiveness of the method.

关 键 词：校园网络安全 网络风险评估 网络风险预测 深度学习 LSTM 

分 类 号：TP393.08[自动化与计算机技术—计算机应用技术] TP18[自动化与计算机技术—计算机科学与技术]