| 应用深度自编码网络的网络安全态势评估 |
| |
| 引用本文： | 张玉臣,张任川,刘璟,汪永伟.应用深度自编码网络的网络安全态势评估[J].计算机工程与应用,2020,56(6):92-98. |
| |
| 作者姓名： | 张玉臣 张任川 刘璟 汪永伟 |
| |
| 作者单位： | 信息工程大学，郑州 450004 |
| |
| 基金项目： | 国家高技术研究发展计划(863) |
| |
| 摘 要： | 针对BP神经网络类方法对标签数据的依赖性缺陷，提出了一种基于深度自动编码网络的态势评估方法。模型应用深度自动编码器作为基本单元构建深度自编码网络，结合专家经验和层次化评估的方法训练深度自编码网络。利用无标签数据采用无监督逐层算法对网络进行预训练，确定网络各层参数及权值的范围空间。在此基础上，采用有监督算法使用有标签样本对网络进行微调，对各层参数及权值进行优化，最终形成具有对输入态势数据进行准确评估能力的模型。多种样本数量条件下的对比实验表明，相对于BP神经网络类方法，基于深度自动编码网络模型受标签的影响较小，明显减少了对专家经验的依赖，并且具有整体上较高的评估精度。
|
| 关 键 词： | 神经网络 态势评估 深度自动编码器 深度自编码网络 标签 |
Network Security Situation Evaluation Using Deep Auto-Encoders Network |
| |
| ZHANG Yuchen,ZHANG Renchuan,LIU Jing,WANG Yongwei.Network Security Situation Evaluation Using Deep Auto-Encoders Network[J].Computer Engineering and Applications,2020,56(6):92-98. |
| |
| Authors: | ZHANG Yuchen ZHANG Renchuan LIU Jing WANG Yongwei |
| |
| Affiliation: | Information Engineering University, Zhengzhou 450004, China |
| |
| Abstract: | Aiming at the defect of the dependence of BP neural network on label data,a situation assessment method based on deep automatic coding network is proposed.The model uses depth auto-encoder as the basic unit to construct depth auto-coding network,and trains depth auto-coding network with expert experience and hierarchical evaluation method.The network is pre-trained by unsupervised layer-by-layer algorithm using unlabeled data to determine the range space of parameters and weights of each layer of the network.Based on this,the network is fine-tuned by using labeled samples with supervised algorithm so that the parameters and weights of each layer are optimized.As a result a model with the ability to accurately evaluate the input situation data is formed.Compared with BP neural network,the deep auto-coding network model is less affected by labels,which significantly reduces the dependence on expert experience,and has a higher overall evaluation accuracy. |
| |
| Keywords: | neural network situation prediction deep automatic encoder deep auto-encoders network tag |
| 本文献已被 维普 万方数据 等数据库收录！ |
| 点击此处可从《计算机工程与应用》浏览原始摘要信息 |
|
点击此处可从《计算机工程与应用》下载全文 |
