| 基于模糊C均值聚类的网络入侵检测算法 |
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| 引用本文： | 杨德刚. 基于模糊C均值聚类的网络入侵检测算法[J]. 计算机科学, 2005, 32(1): 86-87 |
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| 作者姓名： | 杨德刚 |
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| 作者单位： | 重庆大学计算机科学与工程学院,重庆,400030;重庆师范大学数学与计算机科学学院,重庆,400047 |
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| 摘 要： | 入侵检测已成为网络安全的第二层重要防御线。分析了对新型未知的攻击的入侵检测，提出基于模糊C均值聚类的网络入侵检测算法。用KDD-99数据集的仿真实验结果表明算法的可行性、有效性和可扩展性，并有效提高了聚类检测的检测率，降低了误检率。
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| 关 键 词： | 入侵检测 聚类分析 模糊C均值聚类 |
Research of the Network Intrusion Detection Based on Fuzzy Clustering |
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| YANG De-Gang College of Computer Science and Engineering,Chongqing University,Chongqing College of Mathematics and Computer Science,Chongqing Normal University,Chongqing. Research of the Network Intrusion Detection Based on Fuzzy Clustering[J]. Computer Science, 2005, 32(1): 86-87 |
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| Authors: | YANG De-Gang College of Computer Science Engineering Chongqing University Chongqing College of Mathematics Computer Science Chongqing Normal University Chongqing |
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| Affiliation: | YANG De-Gang College of Computer Science and Engineering,Chongqing University,Chongqing 400030 College of Mathematics and Computer Science,Chongqing Normal University,Chongqing 400047 |
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| Abstract: | The intrusion detection become the second floor defense line of the network security. Analyze to the char- acteristic of the intrusion detection technique for newly and unknown attack,and brings forward algorithm of Network Intrusion Detection based on Fuzzy C-means Clustering. The result of simulations run on the KDD-99 datasets show the feasible,efficient and extensible for unknown intrusion detection,and increase detection rate of the clustering de- tection and decrease the false alarms rate. |
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| Keywords: | Intrusion detection Clustering analysis Fuzzy c-means clustering algorithm |
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