| 数据流中孤立点识别方法 |
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| 引用本文： | 单世民,邓贵仕,何英昊. 数据流中孤立点识别方法[J]. 计算机工程, 2007, 33(15): 172-174 |
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| 作者姓名： | 单世民 邓贵仕 何英昊 |
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| 作者单位： | 大连理工大学系统工程研究所,大连,116023;大连理工大学城市学院,大连,116600 |
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| 摘 要： | 针对基于聚类分析及基于孤立点检测的入侵检测方法的局限，根据数据流的特点，提出了一种数据流中孤立点动态识别方法。该方法使用动态微粒群算法对特征空间中当前主要聚类的特征点进行追踪，通过计算数据流中数据对象与特征点的距离来判断数据对象的性质。将该方法应用于入侵检测而进行的实验证明了方法的有效性。
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| 关 键 词： | 数据流 聚类 孤立点检测 微粒群算法 入侵检测 |
| 文章编号： | 1000-3428（2007）15-0172-03 |
| 修稿时间： | 2006-08-20 |
Online Detection Method Towards Outlier in Data Stream |
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| SHAN Shi-min,DENG Gui-shi,HE Ying-hao. Online Detection Method Towards Outlier in Data Stream[J]. Computer Engineering, 2007, 33(15): 172-174 |
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| Authors: | SHAN Shi-min DENG Gui-shi HE Ying-hao |
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| Affiliation: | 1. Institute of Systems Engineering, Dalian University of Technology, Dalian 116023; 2. School of City, Dalian University of Technology, Dalian 116600 |
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| Abstract: | The is paper presents a novel online detection method towards the outlier in data stream.The method is referred as online detection towards outliers in data stream(ODODS).The method is partially inspired by the density based clustering and uses improved adaptive particle swarm optimizer(IAPSO) for detecting the outliers.Results of experiments implemented in intrusion detection domain prove the efficiency of ODODS. |
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| Keywords: | data stream clustering outlier detection PSO intrusion detection |
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