基于大数据的半分布式僵尸网络动态抑制算法

Dynamic Suppression Algorithm of Semi-distributed Zombie Network Based on Big Data

为了提高半分布式僵尸网络的安全性,提出一种基于大数据的半分布式僵尸网络动态抑制算法。采用波特间隔均衡控制方法,进行半分布式僵尸网络的动态特征补偿,构建半分布式僵尸网络动态特征信息采样模型,利用判决均衡方法,对采集到的动态特征信息进行定量递归分析,提取半分布式僵尸网络的统计特征量;在此基础上,采用大数据寻优计算方法,获取真正的半分布式僵尸网络最优抑制参数,在嵌入式环境下,将半分布式僵尸网络的最优抑制参数与迁移负载响应结果相结合,实现半分布式僵尸网络动态抑制。仿真结果表明,采用本文方法进行半分布式僵尸网络动态抑制的效果较好,提高了抑制精度,缩短了抑制时间,且降低了网络输出误码率。

In order to improve the security of semi-distributed botnet,a dynamic suppression algorithm of semi-distributed botnet based on big data is proposed.The method of baud interval equalization control is used to compensate the dynamic characteristics of the semi-distributed botnet.The sampling model of the dynamic characteristics of the semi-distributed botnet is constructed.The decision equalization method is used to analyze the collected dynamic characteristics quantitatively and recursively and extract the statistical characteristics of the semi-distributed botnet.On this basis,the big data optimization calculation method is used to achieve the true optimal suppression of the semi-distributed botnet.Under the embedded environment,the optimal inhibition parameters of the semi-distributed botnet are combined with the results of load response to realize the dynamic inhibition of the semi-distributed botnet.The simulation results show that the semi-distributed botnet dynamic suppression method has a good effect,it improves the suppression precision,shortens the suppression time,and reduces the bit error rate of network output.