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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Main Authors: Wei DING, Jie XU, Weng-hui ZHUO
Format: Article
Language:zho
Published: Editorial Department of Journal on Communications 2014-10-01
Series:Tongxin xuebao
Subjects:
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/
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AT jiexu nettrafficidentifierbasedonhierarchicalclustering
AT wenghuizhuo nettrafficidentifierbasedonhierarchicalclustering