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Computer Engineering ›› 2010, Vol. 36 ›› Issue (18): 19-20. doi: 10.3969/j.issn.1000-3428.2010.18.007

• Networks and Communications • Previous Articles     Next Articles

Two-phase Intrusion Detection Algorithm in Mixed Attributes Data Stream

SU Xiao-ke1, LAN Yang2, QIN Yu-ming1, WAN Ren-xia1, CHENG Yao-dong3   

  1. (1. College of Information Science and Technology, Donghua University, Shanghai 201620, China; 2. School of Computer and Information Technology, Xinyang Normal University, Xinyang 464000, China;3. Computing Center, Institute of High Energy Physics, Chinese Academy of Sciences, Beijing 100049, China)
  • Online:2010-09-20 Published:2010-09-30

混合属性数据流的两阶段入侵检测算法

苏晓珂1,兰 洋2,秦玉明1,万仁霞1,程耀东3   

  1. (1. 东华大学信息科学与技术学院,上海 201620;2. 信阳师范学院计算机与信息技术学院,河南 信阳 464000;3. 中国科学院高能物理研究所计算中心,北京 100049)
  • 作者简介:苏晓珂(1979-),女,博士研究生,主研方向:模式识别,数据挖掘;兰 洋,硕士;秦玉明,教授、博士生导师;万仁霞,博士研究生;程耀东,博士后
  • 基金资助:

    国家“863”计划基金资助项目(2006AA01A120);河南省教育厅自然科学基础研究计划基金资助项目(2010A520033)

Abstract:

This paper proposes a two-phase intrusion detection algorithm in mixed attributes data stream——KDDCUP99-10% network intrusion data set. The algorithm gains the statistical information in data stream by the incremental clustering. Weighted fuzzy clustering is done based on the statistical information according to proposed weighted fuzzy cluster feature. The number of clusters for fuzzy clustering can change dynamically. Theoretical analysis and experimental results show the algorithm can detect the intrusion behaviors effectively.

Key words: mixed attributes, fuzzy clustering, data stream, intrusion detection

摘要:

以KDDCUP99-10%网络入侵数据集作为数据流,提出一种混合属性数据流的两阶段入侵检测算法。通过增量聚类提取数据流的代表信息,根据提出的加权模糊簇特征对增量聚类结果做模糊聚类,簇数可动态改变。理论分析和实验结果表明,该算法可以有效检测数据流入侵。

关键词: 混合属性, 模糊聚类, 数据流, 入侵检测

CLC Number: