基于时间序列的网络安全态势预测方法的研究

互联网上每天充斥着大量入侵与攻击事件,已经严重威胁到网络安全,如何把握网络目前安全态势并预测其发展趋势已成为国内外网络应急响应的热点研究内容之一.根据网络安全事件发生的统计规律性,分别研究了基于时间序列的神经网络和灰色系统理论对未来一段时间内的安全事件数量进行预测的方法,并在此基础上对未来的安全态势进行评估,从而得知网络的整体安全运行状况,有效指导了管理员对网络安全的控制.

The Research on Prediction Method of Network Security Posture Based on Time Series

The Internet is full of a large number of intrusions and attacks every day,which has been a serious threat to network security.How to grasp the current security situation of the network and predict its trend has become one of the hot research contents both at home and abroad.Based on the statistics of network security events,this paper discussed methods of artificial neural network and gray theory,and applied it to the prediction of future security events,and then assessed the security posture in a period of time of future. So that the administrator can be aware of the overall operation condition of the network, and control the network security effectively.