Computer Engineering and Applications ›› 2008, Vol. 44 ›› Issue (11): 127-128.
• 网络、通信、安全 • Previous Articles Next Articles
MA Ru-hui,LIU Yuan,LIN Xing
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马汝辉,刘 渊,林 星
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Abstract: Model of detecting network anomaly based on KQPSO(K-Means Quantum-behaved Particle Swarm Optimization) clustering algorithms is presented.The authors uses K-Means clustering to seed the initial swam.All the process of clustering is based on the Euclidean distance among data vector.Cluster-centroid is chosen by QPSO clustering algorithm.Finally,the experiment result shows that this model is effective for network anomaly detection.
Key words: QPSO(Quantum-behaved Particle Swarm Optimization)algorithm, network anomaly detection, K-Means, K-Means Quantum-behaved Particle Swarm Optimization(KQPSO)
摘要: 提出一种基于KQPSO聚类算法的网络异常检测模型.该模型利用K-Means聚类算法的结果重新初始化粒子群,聚类过程都是根据数据间的Euclidean(欧几里德)距离。再通过量子粒子群优化算法(QPSO)寻找聚类中心。最后进行仿真模拟,实验结果表明,该模型对网络异常检测是有效的。
关键词: QPSO算法, 网络异常检测, K-Means, KQPSO
MA Ru-hui,LIU Yuan,LIN Xing. Network anomaly detection based on KQPSO clustering algorithm[J]. Computer Engineering and Applications, 2008, 44(11): 127-128.
马汝辉,刘 渊,林 星. 基于KQPSO聚类算法的网络异常检测[J]. 计算机工程与应用, 2008, 44(11): 127-128.
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http://cea.ceaj.org/EN/Y2008/V44/I11/127