User-habit based early warning of worm
On the burst-out of massive worm,the overwhelming flow caused by random scanning would temporarily alter the behavior representation of users.Therefore,it was consequently reasonable to conclude that statistics and classify the user habit would certainly help in the detection of worm efficiently.The...
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| Main Authors: | , , , |
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| Format: | Article |
| Language: | zho |
| Published: |
Editorial Department of Journal on Communications
2006-01-01
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| Series: | Tongxin xuebao |
| Subjects: | |
| Online Access: | http://www.joconline.com.cn/zh/article/74667179/ |
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| _version_ | 1841537330316312576 |
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| author | WANG Ping FANG Bin-xing YUN Xiao-chun PENG Da-wei |
| author_facet | WANG Ping FANG Bin-xing YUN Xiao-chun PENG Da-wei |
| author_sort | WANG Ping |
| collection | DOAJ |
| description | On the burst-out of massive worm,the overwhelming flow caused by random scanning would temporarily alter the behavior representation of users.Therefore,it was consequently reasonable to conclude that statistics and classify the user habit would certainly help in the detection of worm efficiently.The behavior of user was analyzed deeply,a new approach for early warning of worms was proposed,and a user-based early warning system was realized.Because of the diversity of user habit,several application models can be derived from the model,it has strong direction signification. |
| format | Article |
| id | doaj-art-aa38e15c4223435e8bd8f26b78ac16b0 |
| institution | Kabale University |
| issn | 1000-436X |
| language | zho |
| publishDate | 2006-01-01 |
| publisher | Editorial Department of Journal on Communications |
| record_format | Article |
| series | Tongxin xuebao |
| spelling | doaj-art-aa38e15c4223435e8bd8f26b78ac16b02025-01-14T08:39:43ZzhoEditorial Department of Journal on CommunicationsTongxin xuebao1000-436X2006-01-01566574667179User-habit based early warning of wormWANG PingFANG Bin-xingYUN Xiao-chunPENG Da-weiOn the burst-out of massive worm,the overwhelming flow caused by random scanning would temporarily alter the behavior representation of users.Therefore,it was consequently reasonable to conclude that statistics and classify the user habit would certainly help in the detection of worm efficiently.The behavior of user was analyzed deeply,a new approach for early warning of worms was proposed,and a user-based early warning system was realized.Because of the diversity of user habit,several application models can be derived from the model,it has strong direction signification.http://www.joconline.com.cn/zh/article/74667179/network securitywormuser habitearly warning |
| spellingShingle | WANG Ping FANG Bin-xing YUN Xiao-chun PENG Da-wei User-habit based early warning of worm Tongxin xuebao network security worm user habit early warning |
| title | User-habit based early warning of worm |
| title_full | User-habit based early warning of worm |
| title_fullStr | User-habit based early warning of worm |
| title_full_unstemmed | User-habit based early warning of worm |
| title_short | User-habit based early warning of worm |
| title_sort | user habit based early warning of worm |
| topic | network security worm user habit early warning |
| url | http://www.joconline.com.cn/zh/article/74667179/ |
| work_keys_str_mv | AT wangping userhabitbasedearlywarningofworm AT fangbinxing userhabitbasedearlywarningofworm AT yunxiaochun userhabitbasedearlywarningofworm AT pengdawei userhabitbasedearlywarningofworm |