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基于卡尔曼滤波的蠕虫检测方法 被引量:1

Approach for Early Detecting Internet Worm Based on Kalman Filtering
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摘要 蠕虫对Internet安全构成了严重威胁,检测和防范蠕虫成为网络安全的研究课题。提出了一种基于卡尔曼滤波的蠕虫检测方法,建立适当的数学模型,给出相应的滤波方程,最后进行仿真分析。该方法可以利用实时量测信息不断地修正估计值。仿真结果表明,采用卡尔曼滤波能够快速有效地检测出蠕虫的爆发。 Internet worm has severely threatened Internet security. To detect and defense the Internet worm becomes an important research topic in the field of network security. The estimator of worm infecting rate was proposed based on the Kalman filtering. The mathematical model was established and the corresponding filter equations were given. The advantage of the method is that the estimate value can be revised constantly. Simulation results show the estimator based on the Kalman filtering is effective and reliable in detecting the Internet worm.
出处 《计算机科学》 CSCD 北大核心 2009年第4期94-96,共3页 Computer Science
基金 国家教育部博士点基金项目(20020699026)资助
关键词 网络安全 蠕虫感染率 卡尔曼滤波 估计 Network security,Worm infecting rate,Kalman filtering, Estimation
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参考文献7

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