基于隐马尔科夫的受攻击光纤网络活跃节点检测方法

Detection method of active nodes in attacked fiber networks based on hidden Markov

传统的受攻击光纤网络活跃节点检测方法通常是被动式的,只能对攻击发生后的行为进行分析,导致检测受攻击活跃节点在光纤网络中的状态值与实际相差较多,为此研究基于隐马尔科夫的受攻击光纤网络活跃节点检测方法。首先对光纤网络活跃节点信号进行去噪处理,通过去噪信号中的数据生成活跃节点特征向量矩阵,进行活跃节点特征融合,在此基础上建立隐马尔科夫受攻击检测模型,定位受攻击光纤网络活跃节点。实验结果表明:该方法在检测受攻击活跃节点在光纤网络中的状态值与实际相接近,精度更高,具有实际的应用价值。

Traditional detection methods of active nodes in attacked fiber networks are usually passive,which can only analyze the behavior after the attack,resulting in a large difference between the status value of the detected active nodes in the attacked fiber networks and the actual value.Therefore,this paper studies the detection method of active nodes in attacked fiber networks based on hidden Markov.Firstly,the signal of active node in optical fiber network is denoised,and the feature vector matrix of active node is generated by the data in the de-noised signal,and the feature fusion of active node is carried out.On this basis,the hidden Markov attack detection model is established to locate the active node in optical fiber network under attack.The experimental results show that this method is close to the actual state value of active nodes under attack in optical fiber networks,and has higher accuracy and practical application value.