Fuzzy clustering method based on genetic algorithm in intrusion detection study
Regarding the problem that fuzzy c-means algorithm（FCM） was sensitive to the initial value and converging to the local infinitesimal point easily, applies genetic algorithm to optimization of the FCM algorithm.Firstly, the results of FCM will be sent to the genetic algorithm for optimization, then t...
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| Format: | Article |
| Language: | zho |
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Editorial Department of Journal on Communications
2009-01-01
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| Series: | Tongxin xuebao |
| Subjects: | |
| Online Access: | http://www.joconline.com.cn/zh/article/74649941/ |
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| Summary: | Regarding the problem that fuzzy c-means algorithm（FCM） was sensitive to the initial value and converging to the local infinitesimal point easily, applies genetic algorithm to optimization of the FCM algorithm.Firstly, the results of FCM will be sent to the genetic algorithm for optimization, then the new results again used in FCM to obtain the most advantage of the overall situation.The experimental result shows that the algorithm can effectively detect anomaly intrusions behavior of special target and be better than FCM algorithm, and have a strong global optimization and faster convergence speed. |
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| ISSN: | 1000-436X |