Net traffic identifier based on hierarchical clustering
An improved net traffic identifier algorithm was proposed based on semi-supervised clustering.Symmetrical uncertainty was used to reduce the net flow attributes,and then kernel function was used to project the rest attributes to higher dimentional space.The train net flow was clustered in high dimen...
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Format: | Article |
Language: | zho |
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Editorial Department of Journal on Communications
2014-10-01
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Series: | Tongxin xuebao |
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Online Access: | http://www.joconline.com.cn/zh/article/doi/10.3969/j.issn.1000-436x.2014.z1.009/ |
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author | Wei DING Jie XU Weng-hui ZHUO |
author_facet | Wei DING Jie XU Weng-hui ZHUO |
author_sort | Wei DING |
collection | DOAJ |
description | An improved net traffic identifier algorithm was proposed based on semi-supervised clustering.Symmetrical uncertainty was used to reduce the net flow attributes,and then kernel function was used to project the rest attributes to higher dimentional space.The train net flow was clustered in high dimentional space hierarchically.Smooth factor,sihouette coefficient and entropy controlled the cluster process to get a well result.Experiments show that the algorithm got flat clusters without any huge cluster and could identify most net flow even encrypted ones. |
format | Article |
id | doaj-art-d40cff541fa94e0cb0c9c36f6594e8eb |
institution | Kabale University |
issn | 1000-436X |
language | zho |
publishDate | 2014-10-01 |
publisher | Editorial Department of Journal on Communications |
record_format | Article |
series | Tongxin xuebao |
spelling | doaj-art-d40cff541fa94e0cb0c9c36f6594e8eb2025-01-14T06:44:46ZzhoEditorial Department of Journal on CommunicationsTongxin xuebao1000-436X2014-10-0135414559688069Net traffic identifier based on hierarchical clusteringWei DINGJie XUWeng-hui ZHUOAn improved net traffic identifier algorithm was proposed based on semi-supervised clustering.Symmetrical uncertainty was used to reduce the net flow attributes,and then kernel function was used to project the rest attributes to higher dimentional space.The train net flow was clustered in high dimentional space hierarchically.Smooth factor,sihouette coefficient and entropy controlled the cluster process to get a well result.Experiments show that the algorithm got flat clusters without any huge cluster and could identify most net flow even encrypted ones.http://www.joconline.com.cn/zh/article/doi/10.3969/j.issn.1000-436x.2014.z1.009/traffic identifyhierarchical clusterkernel functionsihouette coefficient |
spellingShingle | Wei DING Jie XU Weng-hui ZHUO Net traffic identifier based on hierarchical clustering Tongxin xuebao traffic identify hierarchical cluster kernel function sihouette coefficient |
title | Net traffic identifier based on hierarchical clustering |
title_full | Net traffic identifier based on hierarchical clustering |
title_fullStr | Net traffic identifier based on hierarchical clustering |
title_full_unstemmed | Net traffic identifier based on hierarchical clustering |
title_short | Net traffic identifier based on hierarchical clustering |
title_sort | net traffic identifier based on hierarchical clustering |
topic | traffic identify hierarchical cluster kernel function sihouette coefficient |
url | http://www.joconline.com.cn/zh/article/doi/10.3969/j.issn.1000-436x.2014.z1.009/ |
work_keys_str_mv | AT weiding nettrafficidentifierbasedonhierarchicalclustering AT jiexu nettrafficidentifierbasedonhierarchicalclustering AT wenghuizhuo nettrafficidentifierbasedonhierarchicalclustering |