改进的递归神经网络在网络安全态势监测中的应用
On Application of Improved Recurrent Neural Network in Network Security Situation Monitoring
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摘要: 随着网络规模的扩大，组网方式多样化，网络拓扑架构变得更加复杂，网络中的数据流量大规模迅速上升，导致网络负载增大，网络受到的攻击、故障等突发性安全事件更加严峻。该文利用神经网络处理非线性、复杂性等优势，基于改进的递归神经网络预测网络安全态势，实验结果证明该方法运行效率较高，运行结果与实际值相比，误差较低，精确性较高。Abstract: With the expansion and diversification of the network ,network topology structure becomes more complex ,and the data traffic rises rapidly in the network ,which causes the network load increases ,at-tack ,fault and other unexpected severe network security events .Neural network to deal with nonlinear , complexity advantage of this paper ,network security situation prediction based on improved recursive neu-ral networks ,experimental results show that the high efficiency of the method ,results are compared with the actual values ,low error ,high accuracy .
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