Research on a dynamic self-learning efficient intrusion detection model
A dynamic self-learning efficient intrusion detection model was proposed based on inductive reasoning.Ap-plying the method of inductive reasoning into intrusion detection,an incremental inductive reasoning algorithm for intru-sion detection was proposed.This model produced by this algorithm can make...
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| Main Authors: | , , , |
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| Format: | Article |
| Language: | zho |
| Published: |
Editorial Department of Journal on Communications
2007-01-01
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| Series: | Tongxin xuebao |
| Subjects: | |
| Online Access: | http://www.joconline.com.cn/zh/article/74657329/ |
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| _version_ | 1841537503005245440 |
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| author | YANG Wu1 ZHANG Bing2 ZHOU Yuan2 WANG Wei1 |
| author_facet | YANG Wu1 ZHANG Bing2 ZHOU Yuan2 WANG Wei1 |
| author_sort | YANG Wu1 |
| collection | DOAJ |
| description | A dynamic self-learning efficient intrusion detection model was proposed based on inductive reasoning.Ap-plying the method of inductive reasoning into intrusion detection,an incremental inductive reasoning algorithm for intru-sion detection was proposed.This model produced by this algorithm can make self-learning over the ever-emerged new network behavior examples and dynamically modify behavior profile of the model,which overcomes the disadva-ntage that the traditional static detecting model must relearn over all the old and new examples,even can not relearn because of limited memory size.And at the same time,the learning efficiency and detecting efficiency of intrusion detection model are improved greatly. |
| format | Article |
| id | doaj-art-ef62da1ebce94ad6811ddd179131fe17 |
| institution | Kabale University |
| issn | 1000-436X |
| language | zho |
| publishDate | 2007-01-01 |
| publisher | Editorial Department of Journal on Communications |
| record_format | Article |
| series | Tongxin xuebao |
| spelling | doaj-art-ef62da1ebce94ad6811ddd179131fe172025-01-14T08:35:13ZzhoEditorial Department of Journal on CommunicationsTongxin xuebao1000-436X2007-01-01333874657329Research on a dynamic self-learning efficient intrusion detection modelYANG Wu1ZHANG Bing2ZHOU Yuan2WANG Wei1A dynamic self-learning efficient intrusion detection model was proposed based on inductive reasoning.Ap-plying the method of inductive reasoning into intrusion detection,an incremental inductive reasoning algorithm for intru-sion detection was proposed.This model produced by this algorithm can make self-learning over the ever-emerged new network behavior examples and dynamically modify behavior profile of the model,which overcomes the disadva-ntage that the traditional static detecting model must relearn over all the old and new examples,even can not relearn because of limited memory size.And at the same time,the learning efficiency and detecting efficiency of intrusion detection model are improved greatly.http://www.joconline.com.cn/zh/article/74657329/network securityintrusion detectionanomaly detectioninductive reasoningself-learning algorithm |
| spellingShingle | YANG Wu1 ZHANG Bing2 ZHOU Yuan2 WANG Wei1 Research on a dynamic self-learning efficient intrusion detection model Tongxin xuebao network security intrusion detection anomaly detection inductive reasoning self-learning algorithm |
| title | Research on a dynamic self-learning efficient intrusion detection model |
| title_full | Research on a dynamic self-learning efficient intrusion detection model |
| title_fullStr | Research on a dynamic self-learning efficient intrusion detection model |
| title_full_unstemmed | Research on a dynamic self-learning efficient intrusion detection model |
| title_short | Research on a dynamic self-learning efficient intrusion detection model |
| title_sort | research on a dynamic self learning efficient intrusion detection model |
| topic | network security intrusion detection anomaly detection inductive reasoning self-learning algorithm |
| url | http://www.joconline.com.cn/zh/article/74657329/ |
| work_keys_str_mv | AT yangwu1 researchonadynamicselflearningefficientintrusiondetectionmodel AT zhangbing2 researchonadynamicselflearningefficientintrusiondetectionmodel AT zhouyuan2 researchonadynamicselflearningefficientintrusiondetectionmodel AT wangwei1 researchonadynamicselflearningefficientintrusiondetectionmodel |