隐蔽性网络攻击流量监测点高密度部署方法

High Density Deployment Method of Traffic Monitoring Points in Covert Network Attacks

针对网络攻击流量监测精度低,安全性能差的问题,提出一种隐蔽性网络攻击流量监测点高密度部署方法。通过无向图及其节点集、链路集架构成的隐蔽性网络,分析部署代价与运行代价参数指标,依据不同应用要求,设定数据流的监测收益权值;在参数指标的约束条件基础上,完成监测点部署方法架构;根据两步近似算法理念,获得考量准则,为整体部署代价约束条件、整体运行代价与决策变量约束条件的部署策略;经过遗传算法的父系染色体研究与遍历搜索交叉操作,得出相应子染色体,依据其突变产生后代的元素改变数量,完成任意数与预定阈值的分析比较,最终实现监测点的高密度部署。实验结果表明,采用改进的方法进行检测点的部署效果较好,且准确性能更高,具有极强的可行性与适用性。

Due to low accuracy and security of network attack traffic monitoring methods,this article presented a high-density deployment method for traffic monitoring points in covert network attacks.Through the covert network composed of undirected graph,node set and link set,the parameter indexes of deployment cost and operation cost were analyzed.According to different application requirements,the weights of monitoring gain of data flow were set.Based on constraints of parameter indexes,the framework of deployment method of monitoring points was completed.According to the two-step approximate algorithm,the criteria of consideration and discussion was obtained.It was the deployment strategy of cost constraint of overall deployment,overall operation cost and decision variable constraint.Based on the cross operation of paternal chromosome research and traversal search of genetic algorithm,the corresponding daughter chromosome were obtained.According to the number of elemental changes in the offspring generated by mutation,the analysis and comparison of arbitrary number and predetermined threshold were completed.Finally,the high-density deployment for monitoring points was achieved.Simulation results show that the improved method has better deployment effect,higher accuracy,stronger feasibility and better applicability.