基于深度学习的SDN虚拟蜜网路由优化  

SDN Virtual Honeynet Routing Optimization Based on Deep Learning

作　　者：胡洋[1] HU Yang(Airport Management College,Guangzhou Civil Aviation College,Guangzhou 510403,China)

机构地区：[1]广州民航职业技术学院航空港管理学院,广州510403

出　　处：《计算机系统应用》2020年第10期274-279,共6页Computer Systems & Applications

基　　金：2018年度广东省普通高校重点科研平台和科研项目(2018GKTSCX084);广州民航职业技术学院校级科研项目(17X0206)

摘　　要：针对传统蜜网所致的成本昂贵、流量控制不便及动态调整困难等问题,提出使用SDN、ODL与Mininet技术部署轻量级虚拟蜜罐,组建虚拟蜜网拓扑,使用深度学习技术DDPG优化路由选择路径.通过实验表明,优化后的路由选择机制具备动态调整网络结构,有较好的收敛性和选择性.使得网络在遭受攻击时,能将攻击转向蜜网,从而减少攻击造成的危害,增强网络主动防御能力.The traditional honeynet has many drawbacks such as inconvenient deployment,difficult flow control,and complex dynamic adjustment.This study proposes to use SDN,ODL,and Mininet technology to deploy lightweight virtual honeypots,build virtual honeynet topology,and use deep learning technology to optimize route selection.The experimental results show that the proposed SDN routing optimization mechanism has sound convergence and effectiveness,and can turn the attack to honeynet when the network is attacked,so as to reduce the damage caused by the attack and thus reduce the network attack threat.

关 键 词：软件定义网络 深度学习 虚拟蜜网 路由优化 

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]