混合多层结构化网络的攻击路径预测算法研究  

Research on Attack Path Prediction Algorithm for Hybrid Multilayer Structured Networks

作　　者：王婷婷[1] 李晓东[1] 任刚[2] 

机构地区：[1]郑州成功财经学院信息工程系,河南郑州451200 [2]中国科学院软件研究所,北京100190

出　　处：《微电子学与计算机》2017年第4期131-134,共4页Microelectronics & Computer

摘　　要：针对目前的攻击路径预测方法不能准确反映攻击力对后续路径的影响,提出了混合多层结构化网络的攻击路径预测算法.首先,对攻击路径样本时间序列进行组合排序,重新组合产生攻击路径样本,采用极限学习机进行分类训练,然后采用人工鱼群捕鱼算法进行学习机优化,提高对网络攻击路径样本的全局搜素和局部寻优能力,避免陷入局部最优解.最后得到的仿真结果表明,采用该方法进行运动员攻击路径预测的收敛性较好,迭代次数较低,预测精度得到提升.For the current attack path prediction method can not accurately reflect the impact of attack power on the subsequent path,an attack path prediction algorithm is proposed.First of all,the combination of the sort of attack path sample time series,re combination of attack path samples,using extreme learning machine classifier,and then use artificial fish fishing machine learning algorithm was optimized to improve the global search for network attack path samples and local optimization ability and avoid the local optimal solution.The simulation results show that the proposed method has better convergence,lower iteration number and higher prediction accuracy.

关 键 词：混合多层 捕鱼算法 极限学习机 攻击路径 预测 

分 类 号：TP311[自动化与计算机技术—计算机软件与理论]