Method of detecting network anomaly on multi-time-scale
To detect anomaly timely and precisely in high-speed network,an algorithm,named DA-MTS（detecting anomaly on multi-time-scale synchronously）,was proposed.Firstly,pre-process the time series of traffic with non-decimated Haar wavelet transform to produce detail signals,which approximately follow Gauss...
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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/74655858/ |
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| _version_ | 1841537494305210368 |
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| author | WANG Feng-yu1 YUN Xiao-chun1 CAO Zhen-zhong4 |
| author_facet | WANG Feng-yu1 YUN Xiao-chun1 CAO Zhen-zhong4 |
| author_sort | WANG Feng-yu1 |
| collection | DOAJ |
| description | To detect anomaly timely and precisely in high-speed network,an algorithm,named DA-MTS（detecting anomaly on multi-time-scale synchronously）,was proposed.Firstly,pre-process the time series of traffic with non-decimated Haar wavelet transform to produce detail signals,which approximately follow Gaussian white noise.Then detect anomaly based on "3σ" principal of normal distribution.Analysis and experiments reveal that this algorithm can detect anomaly on several time-scales recursively without delay,so it can detect anomaly precisely and timely. |
| format | Article |
| id | doaj-art-d470e7a91fb94dbbb59030abbb59fd82 |
| 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-d470e7a91fb94dbbb59030abbb59fd822025-01-14T08:35:05ZzhoEditorial Department of Journal on CommunicationsTongxin xuebao1000-436X2007-01-01606574655858Method of detecting network anomaly on multi-time-scaleWANG Feng-yu1YUN Xiao-chun1CAO Zhen-zhong4To detect anomaly timely and precisely in high-speed network,an algorithm,named DA-MTS（detecting anomaly on multi-time-scale synchronously）,was proposed.Firstly,pre-process the time series of traffic with non-decimated Haar wavelet transform to produce detail signals,which approximately follow Gaussian white noise.Then detect anomaly based on "3σ" principal of normal distribution.Analysis and experiments reveal that this algorithm can detect anomaly on several time-scales recursively without delay,so it can detect anomaly precisely and timely.http://www.joconline.com.cn/zh/article/74655858/network trafficanomaly detectiontime seriesà trous wavelet transform |
| spellingShingle | WANG Feng-yu1 YUN Xiao-chun1 CAO Zhen-zhong4 Method of detecting network anomaly on multi-time-scale Tongxin xuebao network traffic anomaly detection time series à trous wavelet transform |
| title | Method of detecting network anomaly on multi-time-scale |
| title_full | Method of detecting network anomaly on multi-time-scale |
| title_fullStr | Method of detecting network anomaly on multi-time-scale |
| title_full_unstemmed | Method of detecting network anomaly on multi-time-scale |
| title_short | Method of detecting network anomaly on multi-time-scale |
| title_sort | method of detecting network anomaly on multi time scale |
| topic | network traffic anomaly detection time series à trous wavelet transform |
| url | http://www.joconline.com.cn/zh/article/74655858/ |
| work_keys_str_mv | AT wangfengyu1 methodofdetectingnetworkanomalyonmultitimescale AT yunxiaochun1 methodofdetectingnetworkanomalyonmultitimescale AT caozhenzhong4 methodofdetectingnetworkanomalyonmultitimescale |