基于人工智能技术的光通信网络异流数据检测

Different stream data detection in optical communication network based on artificial intelligence technology

为准确检测光通信网络异流数据,提出基于人工智能技术的光通信网络异流数据检测方法。基于K-means聚类分析光通信网络流数据特征类型,实现特征聚类,预处理去除聚类后的网络流数据特征样本中的冗余特征;将预处理后的特征样本作为识别样本,以识别异常网络流数据特征的形式,检测异流数据。实验结果验证:此方法对多种光通信网络异流数据的检测结果与实际情况一致,具有准确检测光通信网络异流数据能力。

In order to accurately detect the abnormal flow data of optical communication network,a detection method of abnormal flow data of optical communication network based on artificial intelligence technology is proposed.Based on K-means clustering,the characteristic types of optical communication network flow data are analyzed,the characteristic clustering is realized,and the redundant features in the clustered network flow data characteristic samples are pre-processed;The preprocessed feature samples are used as identification samples to identify abnormal network flow data features and detect abnormal flow data.The experimental results show that the detection results of different flow data of various optical communication networks by this method are consistent with the actual situation,and it has the ability to accurately detect different flow data of optical communication networks.