Research on intrusion detection based on an improved GHSOM
A novel technique based on an improved growing hierarchical self-organizing maps（GHSOM） neural network for intrusion detection was presented.The improved GHSOM could deal with a metric incorporating both numerical and symbolic data,and then improved efficiency of intrusion detection.The validities a...
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| Main Authors: | , , , |
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| Format: | Article |
| Language: | zho |
| Published: |
Editorial Department of Journal on Communications
2011-01-01
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| Series: | Tongxin xuebao |
| Subjects: | |
| Online Access: | http://www.joconline.com.cn/zh/article/74419530/ |
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| _version_ | 1841537820216262656 |
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| author | YANG Ya-hui JIANG Dian-bo SHEN Qing-ni XIA Min |
| author_facet | YANG Ya-hui JIANG Dian-bo SHEN Qing-ni XIA Min |
| author_sort | YANG Ya-hui |
| collection | DOAJ |
| description | A novel technique based on an improved growing hierarchical self-organizing maps（GHSOM） neural network for intrusion detection was presented.The improved GHSOM could deal with a metric incorporating both numerical and symbolic data,and then improved efficiency of intrusion detection.The validities and feasibilities of the improved GHSOM were confirmed through experiments on KDD Cup 99 datasets and simulated experiment datasets.The experi-ment results showes that the detection rate has been increased by employing the improved GHSOM. |
| format | Article |
| id | doaj-art-b86b64560cb14a7b890d8be4c213acd3 |
| institution | Kabale University |
| issn | 1000-436X |
| language | zho |
| publishDate | 2011-01-01 |
| publisher | Editorial Department of Journal on Communications |
| record_format | Article |
| series | Tongxin xuebao |
| spelling | doaj-art-b86b64560cb14a7b890d8be4c213acd32025-01-14T08:22:42ZzhoEditorial Department of Journal on CommunicationsTongxin xuebao1000-436X2011-01-013212112674419530Research on intrusion detection based on an improved GHSOMYANG Ya-huiJIANG Dian-boSHEN Qing-niXIA MinA novel technique based on an improved growing hierarchical self-organizing maps（GHSOM） neural network for intrusion detection was presented.The improved GHSOM could deal with a metric incorporating both numerical and symbolic data,and then improved efficiency of intrusion detection.The validities and feasibilities of the improved GHSOM were confirmed through experiments on KDD Cup 99 datasets and simulated experiment datasets.The experi-ment results showes that the detection rate has been increased by employing the improved GHSOM.http://www.joconline.com.cn/zh/article/74419530/network securityintrusion detectionneural networkGHSOM |
| spellingShingle | YANG Ya-hui JIANG Dian-bo SHEN Qing-ni XIA Min Research on intrusion detection based on an improved GHSOM Tongxin xuebao network security intrusion detection neural network GHSOM |
| title | Research on intrusion detection based on an improved GHSOM |
| title_full | Research on intrusion detection based on an improved GHSOM |
| title_fullStr | Research on intrusion detection based on an improved GHSOM |
| title_full_unstemmed | Research on intrusion detection based on an improved GHSOM |
| title_short | Research on intrusion detection based on an improved GHSOM |
| title_sort | research on intrusion detection based on an improved ghsom |
| topic | network security intrusion detection neural network GHSOM |
| url | http://www.joconline.com.cn/zh/article/74419530/ |
| work_keys_str_mv | AT yangyahui researchonintrusiondetectionbasedonanimprovedghsom AT jiangdianbo researchonintrusiondetectionbasedonanimprovedghsom AT shenqingni researchonintrusiondetectionbasedonanimprovedghsom AT xiamin researchonintrusiondetectionbasedonanimprovedghsom |