基于SOA_BP神经网络的网络安全态势预测算法研究

Research on network security situation prediction algorithm based on SOA_BP neural network

当前网络安全形势日益严峻,为了提高网络安全态势预测的准确性,提出了一种基于人群搜索算法优化BP神经网络的网络安全态势预测方法.本算法利用人群搜索算法特有的利己、利他、预动和不确定推理四大行为特征确定搜索策略,找到最佳适应度个体,获取最优权值和阈值,然后再对BP神经网络的随机初始阈值和权值进行赋值,经过神经网络训练后得到预测值,最后与其它两种优化算法得到的预测值进行对比.实验表明,该算法用于网络安全态势预测精准度更高,误差更小,并具有更好的稳定性.

The current cybersecurity situation is getting worse.In order to improve the accuracy of network security situation prediction,a network security situation prediction method based on SOA_BP neural network is proposed.The algorithm uses the four behavioral characteristics of SOA algorithm:the self-interest,altruism,pre-action and uncertainty reasoning to determine the search strategy,find the best fitness individual,obtain the optimal weight and threshold,and then assign them to the random initial weights and thresholds.After training the neural network,the predicted values are obtained.Finally,it is compared with the predicted values obtained by othertwo optimization algorithms.The experimental results show that this prediction algorithm has higher accuracy,smaller error and better stability.