神经网络在计算机网络安全评估中的应用研究

Zhou Lianbing
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引用次数: 4

摘要

本文旨在解决神经网络在计算机网络安全评估中的问题,这对计算机网络的普及具有重要意义。本文提出的计算机网络安全评估系统包含客户端和服务器两部分。客户端模块包括:1)扫描配置模型,2)评估模型,3)扫描结果数据库模型,4)输出模型。服务器由1)扫描引擎、2)漏洞库、3)规则库组成。为了提高人工神经网络的性能,我们选择了反向传播神经网络,并利用粒子群算法进行参数优化。最后,实验结果验证了该方法的有效性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Study on Applying the Neural Network in Computer Network Security Assessment
In this paper, we aim to solve the problem of neural network in computer network security assessment, which is very important for computer network's popularization. Our proposed computer network security assessment system contains client and server. The client module includes: 1) scanning configuration model, 2) assessment model, 3) scanning result database model and 4) output model. Furthermore, server is made up of 1) scanning engine, 2) vulnerability database, 3) rules database. To promote the performance of artificial neural network, we choose the back propagation neural network, and particle swarm optimization is utilized to optimize parameters. Finally, experimental results demonstrate the effectiveness of our proposed approach.
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