摘要
计算机网络在为人们提供各种便利服务的同时也面临着许多的安全威胁,如木马或病毒等。不法分子通过网络攻击,破坏网络服务和用户数据,为人们带来严重的威胁。网络安全专家和企业机构提出了很多安全防御技术,一定程度上提高了网络安全防御能力,但是随着互联网数据和流量的快速增加,网络攻击的种类和数量呈现出指数级增长,急需提出新的防御技术进行应对。本文介绍了一种基于卷积神经网络的安全防御模式,通过入侵检测、数据加密和深度分组过滤等技术,快速定位数据流中是否存在病毒或木马,并及时的对其进行查杀,有效提高网络安全防御的主动性和积极性。
While computer networks provide people with various convenient services,they also face many security threats,such as Trojan horses and viruses.Criminals use network attacks to destroy network services and user data,posing serious threats to people.Network security experts and corporate organizations have proposed many security defense technologies,which have improved network security defense capabilities to a certain extent.However,with the rapid increase in Internet data and traffi c,the types and numbers of network attacks have shown an exponential increase,and there is an urgent need to propose new defense technologies to respond.This article introduces a security defense mode based on convolutional neural networks.Through intrusion detection,data encryption,deep packet fi ltering and other technologies,it can quickly locate whether there are viruses or Trojan horses in the data stream,and check and kill them in time to effectively improve the initiative and enthusiasm of network security defense.
作者
颜慧强
李强
季超凡
YAN Hui-qiang;LI Qiang;JI Chao-fan(China Mobile(Hangzhou)Information Technology Co.,Ltd.,Hangzhou 311121,China)
出处
《电信工程技术与标准化》
2021年第2期89-92,共4页
Telecom Engineering Technics and Standardization
关键词
网络安全
入侵检测
深度分组过滤
人工智能
network security
intrusion detection
deep packet filtering
artificial intelligence
