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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| _version_ | 1841537689221857280 |
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| author | HUANG Min-ming LIN Bo-gang |
| author_facet | HUANG Min-ming LIN Bo-gang |
| author_sort | HUANG Min-ming LIN Bo-gang |
| collection | DOAJ |
| description | 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. |
| format | Article |
| id | doaj-art-9f924a9ce65143e2bcc37417dd38a2fa |
| institution | Kabale University |
| issn | 1000-436X |
| language | zho |
| publishDate | 2009-01-01 |
| publisher | Editorial Department of Journal on Communications |
| record_format | Article |
| series | Tongxin xuebao |
| spelling | doaj-art-9f924a9ce65143e2bcc37417dd38a2fa2025-01-14T08:27:08ZzhoEditorial Department of Journal on CommunicationsTongxin xuebao1000-436X2009-01-013014014574649941Fuzzy clustering method based on genetic algorithm in intrusion detection studyHUANG Min-ming LIN Bo-gangRegarding 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.http://www.joconline.com.cn/zh/article/74649941/intrusion detectionfuzzy C-meansgenetic algorithmglobal optimization |
| spellingShingle | HUANG Min-ming LIN Bo-gang Fuzzy clustering method based on genetic algorithm in intrusion detection study Tongxin xuebao intrusion detection fuzzy C-means genetic algorithm global optimization |
| title | Fuzzy clustering method based on genetic algorithm in intrusion detection study |
| title_full | Fuzzy clustering method based on genetic algorithm in intrusion detection study |
| title_fullStr | Fuzzy clustering method based on genetic algorithm in intrusion detection study |
| title_full_unstemmed | Fuzzy clustering method based on genetic algorithm in intrusion detection study |
| title_short | Fuzzy clustering method based on genetic algorithm in intrusion detection study |
| title_sort | fuzzy clustering method based on genetic algorithm in intrusion detection study |
| topic | intrusion detection fuzzy C-means genetic algorithm global optimization |
| url | http://www.joconline.com.cn/zh/article/74649941/ |
| work_keys_str_mv | AT huangminminglinbogang fuzzyclusteringmethodbasedongeneticalgorithminintrusiondetectionstudy |