计算机科学 ›› 2022, Vol. 49 ›› Issue (6A): 555-561.doi: 10.11896/jsjkx.210800095
杨亚红, 王海瑞
YANG Ya-hong, WANG Hai-rui
摘要: 基于双向的门控循环单元(Bidirectional Gated Recurrent Unit,BiGRU)网络能够解决传统RNN模型存在的梯度消失或梯度爆炸问题,文中提出了一种基于Renyi熵和BiGRU算法实现SDN(Software Defined Network)环境下的DDoS攻击检测方法,首先应用Renyi熵进行异常流量检测,检测划分为正常、异常两种结果,检测为异常的流量将应用BiGRU(bi-gatedrecurrentunit,BiGRU)算法进行攻击检测;然后利用交换机收集流表信息,提取了6个特征向量作为攻击检测的特征向量,最后通过Mininet 模拟SDN的网络拓扑结构,基于控制器OpenDaylight完成检测。实验结果表明:相比SVM和BPNN神经网络检测算法,所提检测方案的检测准确率和识别率更高,有较好的综合检测能力。
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