摘要
网络态势感知关注抽象数据与人能够理解的信息之间的转换技术。其中的网络安全评估跟一般的评估不同之处在于要给管理人员直观的显示和定位,需要自动从网络各种信息中学习。该文设计了一个颜色表示,GIS地理定位,以网络流量信息、报警信息为输入,结合神经网络和网络异常检测(蠕虫、网络攻击)算法的可自学习性的网络状态评估算法。其评价结果经过试运行证明有一定实用性。
Network Situation Awareness(NSA) pays attention to the information transform technology between the abstract data and the knowledge understood by person.Network Security Evaluation of Situation Awareness is different from normal in visualization and auto-learning from network information,for that no expert can give a result to the evaluation.This paper promote a algorithm that result in color,include GIS technique,neural network,network anomaly detection(worm,attack).It can auto-learning.input is netflow and alarm information.The experiment show that is usable in certain environment.
出处
《煤炭技术》
CAS
北大核心
2011年第5期178-180,共3页
Coal Technology
关键词
网络异常检测
网络安全评估
神经网络
态势感知
network anomaly detection
network security evaluation
neural network
situation awareness