摘要
网络安全态势预测是网络安全领域的研究热点之一,在分析当前网络安全态势预测方法的基础上,论文利用Kalman滤波理论建立了网络安全态势预测模型,利用当前和过去时段的攻击强度和网络安全态势值对下一时段的网络安全态势进行预测。实验结果表明该算法的预测精度优于传统的GM(1,1)算法和普通卡尔曼算法(即未结合影响因素),算法适应性和实时性优于RBF算法。
Network security situation prediction is one of current research focuses in the area of network security.In this paper,based on analysing methods to predict network security situation,we apply Kalman filtering to establish a new model which can predict the network security situation.Using the number of attack packets and the value of Network security situation in the present and the past,the method can predict the value of future Network security situation.Experiment results show that the prediction with this method is more precise than GM（1,1） and common kalman algorithm.Its adaptability and performance of real-time is better than that of RBF algorithm.
出处
《计算机与数字工程》
2014年第1期99-102,共4页
Computer & Digital Engineering
关键词
网络安全态势
态势评估
KALMAN滤波
预测
network security situation
situation assessment
Kalman filtering
prediction
作者简介
刘雷雷,女,硕士研究生,研究方向：网络安全.臧洌,女,副教授,研究方向：网络安全、数据库.邱相存,男,硕士研究生,研究方向：实时与嵌入式软件.
